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Swimming speed control and on-board flow sensing of an artificial trout
Abstract
This paper describes a sensing-actuation coupling of a robotic trout that detects changes of the laminar flow speed using an on-board pressure sensor and adjusts its tail-beat frequency for steady swimming. The caudal fin actuator closely mimics the morphology of a real trout, in particular the geometry, stiffness and stiffness distribution of the body and the caudal fin. We hypothesize that the linear relationship between the tail-beat frequency and speed, well-known and proven to hold for all fish studied so far, also holds for an artificial fish. We validate the hypothesis and use the results to derive a linear control law to adjust the tail beat frequency to the swimming speed. We use an onboard pressure sensor to detect the flow speed and test the actuation in a controlled hydrodynamic environment in a flow pipe.
... Nevertheless, the robots are limited to still water and slow speeds, where flow sensing may play a less significant role. One of the earliest robot fish with hydrodynamic sensing capabilities is the prototype under project FILOSE (Robotic FIsh LOcomotion and SEnsing) [123,[127][128][129][130]. In 2011, Kruusmaa et al. reported how a robot fish could use one single pressure sensor to control its tail-beat frequency to keep up with the flow speed in the water channel [123] (figure 5b). ...
... Nevertheless, the robots are limited to still water and slow speeds, where flow sensing may play a less significant role. One of the earliest robot fish with hydrodynamic sensing capabilities is the prototype under project FILOSE (Robotic FIsh LOcomotion and SEnsing) [123,[127][128][129][130]. In 2011, Kruusmaa et al. reported how a robot fish could use one single pressure sensor to control its tail-beat frequency to keep up with the flow speed in the water channel [123] (figure 5b). By incorporating a controller inspired by the Braitenberg vehicle, this robot can perform rheotaxis by sensing the pressure difference between the two sides of its head [128]. ...
... For a pair of robots towed in a [37]. (b-e) Individual robots with flow sensors ( permission from [123] for b, and [124] for c). (d,e) Robots that use flow-sensing to detect their neighbours ( permission from [125] for d, and [126] for e). ...
Collective behaviour defines the lives of many animal species on the Earth. Underwater swarms span several orders of magnitude in size, from coral larvae and krill to tunas and dolphins. Agent-based algorithms have modelled collective movements of animal groups by use of social forces , which approximate the behaviour of individual animals. But details of how swarming individuals interact with the fluid environment are often under-examined. How do fluid forces shape aquatic swarms? How do fish use their flow-sensing capabilities to coordinate with their schooling mates? We propose viewing underwater collective behaviour from the framework of fluid stigmergy , which considers both physical interactions and information transfer in fluid environments. Understanding the role of hydrodynamics in aquatic collectives requires multi-disciplinary efforts across fluid mechanics, biology and biomimetic robotics. To facilitate future collaborations, we synthesize key studies in these fields.
... (c) ALL system developed by Fuentes-Pérez et al. [5]. (d) Sensing-actuation coupling of a robotic trout described by Kruusmaa et al. [31]. ...
... For the speed control strategy, Kruusmaa et al. [31] developed a sensing-actuation robotic trout that detected the fluctuations of flow velocity through pressure sensor and adjusted its tail-beat frequency to remain stationary in the uniform flow (Figure 10(d)). They used the same pressure sensors as Salumäe. ...
... Kruusmaa et al. [31] 2 pressure sensors ...
Lateral line is a system of sense organs that can aid fishes to maneuver in a dark environment. Artificial lateral line (ALL) imitates the structure of lateral line in fishes and provides invaluable means for underwater-sensing technology and robot fish control. This paper reviews ALL, including sensor fabrication and applications to robot fish. The biophysics of lateral line are first introduced to enhance the understanding of lateral line structure and function. The design and fabrication of an ALL sensor on the basis of various sensing principles are then presented. ALL systems are collections of sensors that include carrier and control circuit. Their structure and hydrodynamic detection are reviewed. Finally, further research trends and existing problems of ALL are discussed.
... The first important aspect is the sensory modality, i.e. the type of the sensed physical phenomenon, such as visual (light) [20 -27,32,33,35-46], somatosensory (touch and perception) [47,48,49,[50][51][52][53][54][55][56][58][59][60][61][62][63][64][65][66][67][68], auditory (hearing) [71,72] and even electric [73][74][75][76][77] or magnetic field [78,79]. Some researchers also investigated sensor morphology of multimodal systems, where a combination of multiple sensors is used, each sensing a different physical phenomenon [80][81][82][83][84]. ...
... Mechanical dynamics also help sensing processes underwater. A commercially available on-board pressure sensor was used in a robotic trout with bioinspired morphology to detect the laminar flow speed [54,55]. It was shown that owing to the similar mechanical dynamics arising from the interaction between the robot's body and the environment, it was possible to derive a linear control law between the tail-beat frequency and the swimming speed, which holds for both the real and artificial fish. ...
Sensor morphology, the morphology of a sensing mechanism which plays a role of shaping the desired response from physical stimuli from surroundings to generate signals usable as sensory information, is one of the key common aspects of sensing processes. This paper presents a structured review of researches on bioinspired sensor morphology implemented in robotic systems, and discusses the fundamental design principles. Based on literature review, we propose two key arguments: First, owing to its synthetic nature, biologically inspired robotics approach is a unique and powerful methodology to understand the role of sensor morphology and how it can evolve and adapt to its task and environment. Second, a consideration of an integrative view of perception by looking into multidisciplinary and overarching mechanisms of sensor morphology adaptation across biology and engineering enables us to extract relevant design principles that are important to extend our understanding of the unfinished concepts in sensing and perception. © 2016 The Author(s) Published by the Royal Society. All rights reserved.
... Pa range. 118 119Bernoulli approach (Dubois et al., 1974; Kruusmaa et al., 2011; Salumäe & Kruusmaa, 138 2013). This method uses the Pitot equation derived from Bernoulli's principle, which 139 considers pressure differences between a stagnation point (P 1 ) and a second point on 140 the same body which registers the free-stream static pressure (P 2 ). ...
... The motor of the flume creates 254 recirculation of the water inside the tank and the flow is made uniform by means of 255 two collimators. The flume is able to generate flow speeds over a range 0.05 to 0.50 256 m/s with a mean accuracy of 0.04 m/s (Kruusmaa et al., 2011). 257 258 pressure readings were registered in flow steps of 0.05 m/s over the full range of 263 speeds of the flume. ...
Freshwater ecosystems are inhabited by a vast spectrum of organisms, each with their own complex biotic–abiotic relations. Considering the management and conservation of these environments, it is necessary to understand the underlying hydrodynamic interactions to which aquatic organisms are subject. Outside of bulk flow properties such as the time-averaged velocity, it is currently difficult or impossible to obtain detailed observations of the fluid–body interaction using current measurement technology. It is in this context that the lateral line probe (LLP) has been developed. The LLP mimics the performance of flow sensing modalities present in many aquatic vertebrates. Research in the last decade has demonstrated that such devices are able to reproduce signals relevant to fish behavior and estimate the hydrodynamic stimulus response of the lateral line. However in most cases, the application of LLPs have been limited to idealized conditions, subject to rigorous calibration. In this paper we present an algorithm that allows the use of LLPs for current velocity estimation without sensor calibration. The method makes use of the fluctuations in the near-body pressure field induced by fluid–body interactions and introduces a semi-empirical resampling process based on the conservation of energy. The algorithm is calibrated using a closed flume and measurements taken using a laser Doppler anemometer. Validation of the approach is carried out by comparing results obtained with an acoustic Doppler velocimeter (ADV) in a vertical slot fishway. The mean error as compared to direct measurements with the ADV was found to be 0.11 m/s with a correlation of 0.92.
... Inspired by this biological mechanism, researchers have developed various artificial lateral line (ALL) systems to enhance underwater sensing capabilities in robots [6]- [10]. Applications using ALL systems [11]- [14] such as obstacle avoidance [15]- [17], station holding [18], [19], and localization [20], [21], have been successfully implemented. ...
The artificial lateral line (ALL) is a bioinspired flow sensing system for underwater robots, comprising of distributed flow sensors. The ALL has been successfully applied to detect the undulatory flow fields generated by body undulation and tail-flapping of bioinspired robotic fish. However, its feasibility and performance in sensing the undulatory flow fields produced by human leg kicks during swimming has not been systematically tested and studied. This paper presents a novel sensing framework to investigate the undulatory flow field generated by swimmer's leg kicks, leveraging bioinspired ALL sensing. To evaluate the feasibility of using the ALL system for sensing the undulatory flow fields generated by swimmer leg kicks, this paper designs an experimental platform integrating an ALL system and a lab-fabricated human leg model. To enhance the accuracy of flow sensing, this paper proposes a feature extraction method that dynamically fuses time-domain and time-frequency characteristics. Specifically, time-domain features are extracted using one-dimensional convolutional neural networks and bidirectional long short-term memory networks (1DCNN-BiLSTM), while time-frequency features are extracted using short-term Fourier transform and two-dimensional convolutional neural networks (STFT-2DCNN). These features are then dynamically fused based on attention mechanisms to achieve accurate sensing of the undulatory flow field. Furthermore, extensive experiments are conducted to test various scenarios inspired by human swimming, such as leg kick pattern recognition and kicking leg localization, achieving satisfactory results.
... The fin propulsion system could generate lift, drag, and acceleration-reaction forces (Fish 2004, Babu et al 2014. Further, the cruising speed of fish and its biomimetic model has a linear relationship with its fin frequency (Roberts et al 1992, Doyle and Roberts 2006, Kruusmaa et al 2011, Berlinger et al 2021. The performance of a biomimetic AUV with a BCF mechanism could then be assessed using the forces it generates in a certain fin frequency. ...
Biomimetic fin propulsion could be a promising solution for an efficient underwater propulsion mechanism. It could be designed to efficiently generate thrust for underwater locomotion. Many studies have proposed that the flexibility characteristics of the fin affect its effectiveness in thrust generation; for example, a flexible fin generates more thrust than a rigid fin. In this regard, the rigid fin may suffer a mechanical disadvantage in thrust generation. This study introduces the presence of thrust generation phases in biomimetic fins. The phases could be caused by the interaction of the fins and the surrounding fluid. To distinguish the phases clearly, the experimental setup in this study was designed for no-flow conditions. This study presents three phases of thrust generation: negative, transition, and positive. The existence of the negative and transition phases explains the mechanical disadvantages of the rigid fin. Within the range of evaluated fin frequencies, approximately 80% of the average net force of the rigid fin is in the negative and transition phases, compared to only 20% in flexible fins. In comparison to less flexible and rigid fins, a flexible fin could maximize positive thrust production three times higher at high frequency. The vector composition analysis and dye-injection flow visualization reveal the transition phase by emphasizing the balancing process between the surface friction of the fin and the inertial component of the force of the fluid and fin interaction. This study demonstrates the independence of the transition phase from the flexibility characteristics of the biomimetic fin. Because the bending characteristic of the flexible fin could direct more vectors in thrust generation, the fin could act as a thrust vectoring agent. The findings of this study could be used as a guide in designing and implementing high-performance fin propulsion in low-speed underwater locomotion.
... The validation was realized in two tests, one in a closed flow tunnel and second in field. The flow tunnel experiments were done with 11 different speeds for 5 repetitions with 1 min samples (overview of flow tunnel can be found in Kruusmaa et al. (2011). The field validation was done by dragging the hydromast finned module on a pier with 3 varying velocities for 5 min periods. ...
Currents flowing through aquaculture farms are essential to guarantee quality of the produced fish. Water flow through the fish farms transport fresh oxygen in and at the same time, waste out from the cages. Previous studies have shown that the flow speed inside the cages affects the growth rate of the fish and that it is equally important to measure flow conditions outside the farm and inside the cages. We demonstrate the usage of cost effective flow meter, hydromast, as a possible monitoring device for currents inside agriculture fish cages. In this study we validate the hydromast performance in the noisy environment and demonstrate in field experiments, that the device can be used to measure tidal currents online in fish cages with a distributed suspended array.
... A review of biomimetic robotic fish, their gaits and actuators is provided in [21]. The eel gait (Anguilliform) is most suitable for the current eel-like body of RoboFish, and the trout gait (Subcarangieform) is more likely to show instability in this kind of robot than robotic fish with a trout-like body [22]. The eel gait is used in many similar robot fish and is well known in the literature. ...
To reduce human risk and maintenance costs, Autonomous Underwater Vehicles (AUVs) are involved in subsea inspections and measurements for a wide range of marine industries such as offshore wind farms and other underwater infrastructure. Most of these inspections may require levels of manoeuvrability similar to what can be achieved by tethered vehicles, called Remotely Operated Vehicles (ROVs). To extend AUV intervention time and perform closer inspection in constrained spaces, AUVs need to be more efficient and flexible by being able to undulate around physical constraints. A biomimetic fish-like AUV known as RoboFish has been designed to mimic propulsion techniques observed in nature to provide high thrust efficiency and agility to navigate its way autonomously around complex underwater structures. Building upon advances in acoustic communications, computer vision, electronics and autonomy technologies, RoboFish aims to provide a solution to such critical inspections. This paper introduces the first RoboFish prototype that comprises cost-effective 3D printed modules joined together with innovative magnetic coupling joints and a modular software framework. Initial testing shows that the preliminary working prototype is functional in terms of water-tightness, propulsion, body control and communication using acoustics, with visual localisation and mapping capability.
... Kruusmaa et al. implemented rheotaxis behaviour in robotic fish in 2011. With the pressure sensors detecting flow information, they put forward a linear control law which helped the robotic fish to adjust the beat frequency in order to maintain position in the steady flow [92] . In 2013, they used a 50-cm-long robotic fish (Fig. 10b) mimicking the geometry and swimming mode of a rainbow trout and put forward a formula for estimating the speed. ...
Any phenomenon in nature is potential to be an inspiration for us to propose new
ideas. Lateral line is a typical example which has attracted more interest in recent
years. With the aid of lateral line, fish is capable of acquiring fluid information around,
which is of great significance for them to survive, communicate and hunt underwater. In
this paper, we briefly introduce the morphology and mechanism of the lateral line first.
Then we focus on the development of artificial lateral line which typically consists of an
array of sensors and can be installed on underwater robots. A series of sensors
inspired by the lateral line with different sensing principles have been summarized. And
then the applications of artificial lateral line system in hydrodynamic environment
sensing and vortices detection, dipole oscillation source detection, and autonomous
control of underwater robots have been surveyed. In addition, the existing problems
and future foci in the field have been further discussed in detail. The current works and
future foci have demonstrated that artificial lateral line has great potentials of research
and contributes to the applications of underwater robots
... In this paper, we propose a low-cost, small-sized, and energyefficient technology for estimating surge velocity based on differential pressure sensors. The proposed solution builds upon our previous work, which was originally bioinspired by fish lateral line sensing [20]. Several artificial lateral line systems have been proposed earlier [21], [22], but none of them has been combined with a fully autonomous AUV and, to the best of the authors' knowledge, none have been tested outside of the carefully controlled laboratory environment. ...
Velocity estimation is central for the reliable navigation of autonomous underwater vehicles (AUVs). Doppler velocity logs (DVLs), currently the leading technology for underwater velocity estimation, can be too big, expensive, and energy consuming to be used on low-cost and small AUVs or for long missions. In our previous work, a system based on differential pressure sensors was developed for estimating surge velocity. In this paper, we combine this system with an inertial measurement unit to compensate for orientation errors and create a differential pressure sensor speedometer (DPSS). We propose and demonstrate the DPSS prototype as an important step toward a small, inexpensive, and energy-efficient alternative or complement to a DVL in certain applications. This paper presents the first underwater field tests of a sensor using differential pressure for velocity estimation. Tests were conducted with a SPARUS II AUV (IQUA Robotics, Girona, Spain). To demonstrate the efficacy of our proposed solution, we compare the surge velocity estimation of the DPSS and the vehicle's DVL in bottom and water locks. Trials were conducted by varying the trajectory and velocity of the vehicle in three different environments. We show that the DPSS displayed a superior performance with respect to the DVL water lock for velocities above 0.6 m/s. The differences in the velocity estimations of the DVL in bottom lock for high velocities were as small as 0.013 m/s. These results encourage further development of the presented technology.
... According to our previous studies with a fixed robotic fish with pressure sensors, the flow speed can be estimated by the pressure drop on the sides of the robot or by the pressure difference between the tip of the nose and on the bottom [25]. Here we study whether the same relations hold for the freely swimming robot and whether it can estimate the speed of the robotic fish in still water. ...
Many species of fish use the lateral line for underwater information extraction. In spite of the extensive work on artificial lateral line (ALL) and inertial measurement unit (IMU), the ALL and IMU are rarely used together to estimate the speed of robotic fish. Here we show that an artificial lateral line and an inertial measurement unit can be used cooperatively to estimate the speed of a swimming robotic fish. Based on the analysis of the robotic fish, we use an optimal information fusion decentralized filter algorithm to efficiently fuse the information of ALL and IMU for speed estimation. Our robotic fish has an artificial lateral line consisting of 11 pressure sensors and an inertial measurement unit. Experiments conducted with the freely swimming robotic fish demonstrate that the proposed scheme is able to efficiently estimate the robot speed with small errors in real time.
... Starting with the steady current, we developed methodology to measure the orientation of the vehicle with respect to the flow and showed that even a simple Braitenberg controller can be used to achieve stable rheotactic behavior [143]. Also, we developed approach for estimating flow speed and holding down-stream position [144], [150]. Moving from steady flow to disturbed flow, we developed an approach to identify and localize the upstream object using an artificial lateral line. ...
... For example, Fei et al. [45] and Tokutake et al. [171] utilized thermal air flow sensors on the wings of small unmanned aircrafts for the detection of flight parameters including the airspeed based on a neural network and piecewise quadratic regression, respectively. Kruusmaa et al. [92] determined the optimal position of pressure sensors on an artificial trout to estimate the velocity using a quadratic regression model. For attitude estimation, Euston et al. [44] fused IMU and airspeed measurements of a UAV. ...
In recent years, embedded systems have become popular, and, for example, consumer electronics, transportation, and robotics are hard to imagine without them. As mobile devices with embedded systems are often supposed to act intelligently, they are usually equipped with sensors and actuators for interaction with humans or for autonomous operation. However, cost pressure and miniaturization impose several challenges on embedded devices. They have to be designed in an energy-efficient way and therefore have limited computational power, which is often paired with weak actuators and limited sensing capabilities.
In this thesis, we show how to cope with these challenges using the example of autonomous navigation for miniature indoor airships. Such airships have become popular, because they can navigate safely through three-dimensional environments and operate in long-term navigation tasks. We present the design and the implementation of a miniature indoor blimp and several novel techniques for effective autonomous navigation.
In particular, we introduce techniques for robust online localization of miniature airships in known, complex indoor environments. We present a particle filter implementation for probabilistic state estimation of airships equipped with lightweight sonar and air flow sensors as well as an IMU. We introduce probabilistic models dedicated to the miniature and lightweight sensors applied on our blimp. In contrast to other approaches, our models explicitly consider the uncertainty of the measurement process and therefore specify appropriate measurement likelihood functions that enable a robust localization of the blimp. Furthermore, we show that the simultaneous estimation of motion model parameters is beneficial to the localization accuracy and enables to adapt to changing parameters of the system dynamics during operation. We achieve a robust and efficient online localization by introducing an efficient probabilistic odometry motion model based on the measurements of air flow sensors and an IMU. Particularly, our linear odometry model is substantially less computationally demanding than the standard physical simulation-based motion model and decreases the dimensionality of the state space in the particle filter.
In addition to our solutions to online self-localization, we introduce an effective approach to planning and closed-loop control for autonomous navigation. Our method efficiently solves the high-dimensional, kinodynamic planning and control problem, which is imposed by airships with weak actuators, through a multi-stage planner and an LQR controller. In contrast to other approaches, our planning algorithm performs path-guided sampling and selects optimal actions towards subgoals and therefore can quickly provide a partial trajectory, which is extended during operation.
We implemented and thoroughly tested our novel methods in extensive experiments in simulation and with real robots. We validated the properties of our algorithms and demonstrated the advantages of our approaches compared to state-of-the-art methods. While the work as a whole aims at the autonomous navigation for miniature airships, the individual algorithms and techniques presented in this thesis are often applicable to a variety of problems. Therefore, we believe that the proposed methods are relevant for future low-cost, small, and resource-constrained embedded systems with applications in industrial settings and everyday life.
... Such sensory systems which are capable of providing a continuous sensing of flows and flow generated pressures around the bodies of underwater robots can greatly benefit the maneuverability and object avoidance strategies of the ocean-going vehicles [12,15,16]. Some studies in the past have utilized such sensory systems for detecting hydrodynamic wake signatures and thereby for controlling the robot's motion with respect to the flow [15,17]. In real-time, there is a wide range of frequencies that underwater creatures might experience. ...
A major difference between manmade underwater robotic vehicles (URVs) and undersea animals is the dense arrays of sensors on the body of the latter which enable them to execute extreme control of their limbs and demonstrate super-maneuverability. There is a high demand for miniaturized, low-powered, lightweight and robust sensors that can perform sensing on URVs to improve their control and maneuverability. In this paper, we present the design, fabrication and experimental testing of two types of microelectromechanical systems (MEMS) sensors that benefit the situational awareness and control of a robotic stingray. The first one is a piezoresistive liquid crystal polymer haircell flow sensor which is employed to determine the velocity of propagation of the stingray. The second one is Pb(Zr0.52Ti0.48)O3 piezoelectric micro-diaphragm pressure sensor which measures various flapping parameters of the stingray’s fins that are key parameters to control the robot locomotion. The polymer flow sensors determine that by increasing the flapping frequency of the fins from 0.5 to 3 Hz the average velocity of the stingray increases from 0.05 to 0.4 BL s⁻¹, respectively. The role of these sensors in detecting errors in control and functioning of the actuators in performing tasks like flapping at a desired amplitude and frequency, swimming at a desired velocity and direction are quantified. The proposed sensors are also used to provide inputs for a model predictive control which allows the robot to track a desired trajectory. Although a robotic stingray is used as a platform to emphasize the role of the MEMS sensors, the applications can be extended to most URVs.
... From our previous studies with a fixed robotic fish with pressure sensors, we know that the flow speed can be estimated by the pressure drop on the sides of the robot or by the pressure difference between the tip of the nose and on the sides [32]. Here, we study if the same relations hold for the freely swimming robot and if they can be used to design a controller for station holding. ...
This paper describes flow-relative and flow-aided navigation of a biomimetic underwater vehicle using an artificial lateral line for flow sensing. Most of the aquatic animals have flow sensing organs, but there are no man-made analogues to those sensors currently in use on underwater vehicles. Here, we show that artificial lateral line sensing can be used for detecting hydrodynamic regimens and for controlling the robot's motion with respect to the flow. We implement station holding of an underwater vehicle in a steady stream and in the wake of a bluff object. We show that lateral line sensing can provide a speed estimate of an underwater robot thus functioning as a short-term odometry for robot navigation. We also demonstrate navigation with respect to the flow in periodic turbulence and show that controlling the position of the robot in the reduced flow zone in the wake of an object reduces a vehicle's energy consumption.
... For example, Fei et al. [9] and Tokutake et al. [22] utilize thermal flow sensors on the wings of small unmanned aircrafts for the detection of flight parameters including the airspeed. Kruusmaa et al. [14] determine the optimal position of pressure sensors on an artificial trout to estimate the velocity using a quadratic regression model. For attitude estimation, Euston et al. [8] fuse IMU and airspeed measurements of a UAV. ...
Recently, autonomous miniature airships have become a growing research field. Whereas airships are attractive as they can move freely in the three-dimensional space, their high-dimensional state space and the restriction to small and lightweight sensors are demanding constraints with respect to self-localization. Furthermore, their complex second-order kinematics makes the estimation of their pose and velocity through dead reckoning odometry difficult and imprecise. In this paper, we consider the problem of estimating the velocity of a miniature blimp with lightweight air flow sensors. We present a probabilistic sensor model that accurately models the uncertainty of the flow sensors and thus allows for robust state estimation using a particle filter. In experiments carried out with a real airship we demonstrate that our method precisely estimates the velocity of the blimp and outperforms the standard velocity estimates of the motion model as applied in many existent autonomous blimp navigation systems.
... July/August 2011 Volume 45 Number 4 propel a 0.7-m long robotic electric ray (Krishnamurthy et al., 2010), a 0.5-m long robotic trout (Kruusmaa et al., 2011 ), a 0.12-m long mechanical sunfish (McHenry et al., 1995), and a 0.5-m long mechanical pickerel (Conte et al., 2010). Of these self-propelled aquatic vehicles, only the mechanical pickerel has anything resembling a vertebral column: a piece of spring steel designed to release mechanical work to power accelerations. ...
The vertebral column is the primary stiffening element of the body of fish. This serially jointed axial support system offers mechanical control of body bending through kinematic constraint and viscoelastic behavior. Because of the functional importance of the vertebral column in the body undulations that power swimming, we targeted the vertebral column of cartilaginous fishes—sharks, skates, and rays—for biomimetic replication. We examined the anatomy and mechanical properties of shark vertebral columns. Based on the vertebral anatomy, we built two classes of biomimetic vertebral column (BVC): (1) one in which the shape of the vertebrae varied and all else was held constant and (2) one in which the axial length of the invertebral joint varied and all else was held constant. Viscoelastic properties of the BVCs were compared to those of sharks at physiological bending frequencies. The BVCs with variable joint lengths were then used to build a propulsive tail, consisting of the BVC, a vertical septum, and a rigid caudal fin. The tail, in turn, was used as the propeller in a surface-swimming robot that was itself modeled after a biological system. As the BVC becomes stiffer, swimming speed of the robot increases, all else being equal. In addition, stiffer BVCs give the robot a longer stride length, the distance traveled in one cycle of the flapping tail.
The artificial lateral line (ALL) is a bioinspired flow sensing system for underwater robots, comprising of distributed flow sensors. The ALL has been successfully applied to detect the undulatory flow fields generated by body undulation and tail-flapping of bioinspired robotic fish. However, its feasibility and performance in sensing the undulatory flow fields produced by human leg kicks during swimming have not been systematically tested and studied. This paper presents a novel sensing framework to investigate the undulatory flow field generated by swimmer’s leg kicks, leveraging bioinspired ALL sensing. To evaluate the feasibility of using the ALL system for sensing the undulatory flow fields generated by swimmer leg kicks, this paper designs an experimental platform integrating an ALL system and a lab-fabricated human leg model. To enhance the accuracy of flow sensing, this paper proposes a feature extraction method that dynamically fuses time-domain and time-frequency characteristics. Specifically, time-domain features are extracted using one-dimensional convolutional neural networks and bidirectional long short-term memory networks (1DCNN-BiLSTM), while time-frequency features are extracted using short-term Fourier transform and two-dimensional convolutional neural networks (STFT-2DCNN). These features are then dynamically fused based on attention mechanisms to achieve accurate sensing of the undulatory flow field. Furthermore, extensive experiments are conducted to test various scenarios inspired by human swimming, such as leg kick pattern recognition and kicking leg localization, achieving satisfactory results.
The lateral line plays a crucial role as a sensory organ in fish for detecting and interpreting flow field environments. Taking inspiration from the lateral line of fish, this study investigates the implementation of an artificial lateral line system on a biomimetic fish-shaped Unmanned Underwater Vehicle (UUV). To ensure accurate positioning of the UUV while considering physical dimensions, cost, and environmental friendliness (by avoiding the use of sonar), we propose a fusion method based on factor graph optimization that combines data from an Inertial Measurement Unit (IMU) and the artificial lateral line system (ALLS). This method integrates velocity information obtained from the artificial lateral lines with attitude information provided by the IMU, enabling the UUV to achieve precise self-positioning at a relatively low cost. Water tank experiments demonstrate the significant improvement in the UUV’s trajectory estimation ability achieved by our proposed method.
The lateral line organs of fish presents a promising idea for achieving near-field target awareness. Inspired by the localization of targets by fish, a neural network approach to localize underwater vibration sources is a feasible technical approach. However, previous methods using neural networks are relatively simple, and the robustness of the model is weak. Moreover, the previous studies only focused on single-source localization problems, which were inconsistent with the reality of multiple vibration sources in underwater environments. To address these issues, we develop an artificial lateral system with integrated pressure sensors for acquiring pressure transform signals from underwater multi-source vibrations. A novel attention mechanism-based multi-sensing multi-source feature fusion network (AMSS-FFN) is proposed to exploit the information of data fully. Specifically, to reflect the superiority of convolutional neural networks for extracting image features, we transform the one-dimensional signal into a two-dimensional grey-scale image and a time-frequency image processed by Stockwell transformer. Furthermore, a hybrid attention mechanism that learns channel and location information is introduced, allowing globally important features to be represented. Finally, we employ a dynamic learning strategy to fuse features in the time and time-frequency domains. The effectiveness of the method is verified using a laboratory-measured dataset. The results indicate that the prediction accuracy of the proposed method is significantly improved.
We introduce the lateral line probe (LLP) as a measurement device for natural flows. Hydraulic surveys in rivers and hydraulic structures are currently based on time-averaged velocity measurements using propellers or acoustic Doppler devices. The long-term goal is thus to develop a sensor system, which includes spatial gradients of the flow field along a fish-shaped sensor body. Interpreting the biological relevance of a collection of point velocity measurements is complicated by the fact that fish and other aquatic vertebrates experience the flow field through highly dynamic fluid-body interactions. To collect body-centric flow data, a bioinspired fish-shaped probe is equipped with a lateral line pressure sensing array, which can be applied both in the laboratory and in the field. Our objective is to introduce a new type of measurement device for body-centric data and compare its output to estimates of conventional point-based technologies. We first provide the calibration workflow for laboratory investigations. We then provide a review of two velocity estimation workflows, independent of calibration. Such workflows are required as existing field investigations consist of measurements in environments where calibration is not feasible. The mean difference for uncalibrated LLP velocity estimates from 0 to 50 cm/s under in a closed flow tunnel and open channel flume was within 4 cm/s when compared to conventional measurement techniques. Finally, spatial flow maps in a scale vertical slot fishway are compared for the LLP, direct measurements, and 3D numerical models where it was found that the LLP provided a slight overestimation of the current velocity in the jet and underestimated the velocity in the recirculation zone.
Based on pressure sensor, a speed estimation method for robotic fish is presented in this paper. Based on property of pressure sensor, the relation model between pressure and speed is fitted by experimental analysis. Using this relation model, the swimming speed of robotic fish can be calculated by pressure. A validation experiment was conducted with a freely swimming robot. The experiment results demonstrated the feasibility and accuracy of this measure method, which providing a new way to measure the swimming speed of robotic fish.
This paper describes an underwater robot navigation strategy in flow. Our aim is to demonstrate that knowing the relative flow speed is advantageous because it permits using more energy efficient and stable control for trajectory following. We use a biomimetic robot that moves in uniform flow using a side-slipping maneuver. Side-slipping permits the robot to move laterally with respect to the incoming flow by exploiting its passive dynamics. The side-slipping maneuver is controlled by adjusting the heading of the robot with respect to the flow. We implement simple PID controllers for controlling the motion of the side-slipping robot laterally and transversely. Also, we compare the performance of the robot in the case where the robot does not know the flow speed. In this latter case the robot's heading towards the waypoint is controlled and the flow effect is considered as a disturbance compensated by the control algorithm. Comparative experiments demonstrate that it is advantageous for a robot to know not just its speed and orientation with respect to the world's frame of reference but also its local flow-relative speed. It permits the robot to follow trajectories more stable and using less energy. In the discussion section we propose possible future directions for implementing the on board flow-relative control.
In this work we report the design and development of a biomimetic waterproof Si/SiN multilayered cantilever whose internal stress gradient bends the beam out of the plane enabling flow velocity detection in water. A water resistant parylene conformal coating has been deposited on the artificial hair cell for waterproof operation. The sensing mechanism is represented by a piezoresistive strain-gauge along the cantilever beam. A set-up for analysing sensor responsivity in air and water has been used and its electrical behavior is reported. Responsivity of 0.7 mV/(cm/s) is recorded and a linear response of sensor read-out signal amplitude with respect to flow pulses up to 30 Hz. Parylene conformal coating is demonstrated to be an efficient method for water sealing and can be effective in the post-fabrication for tuning the micromechanical cantilever properties.
During swimming at constant speed the frequency (f), amplitude (a) and depth (d) of the tail trailing edge, and the length of the propulsive wave (λ) were measured for rainbow trout ranging in total length (L) from 5·5 to 56·0 cm. Fish were tested in a water flume using increasing velocity tests to sample a range of swimming speeds, V. λ was independent of V and related to size by: so that wavelength was relatively larger in smaller fish. 3.f was related to L and V according to: a was independent of V but was relatively smaller in larger fish: d was also independent of V but relatively larger in larger fish: Thrust power (= drag power) calculated using Lighthill’s small amplitude bulk momentum model was two to three times the theoretical minimum of a flat plate of equivalent length and area moving parallel to the flow with a presumed turbulent boundary layer. Froude efficiency increased with swimming speed, and it is shown that this is the usual relationship for fish studied so far. Froude efficiency was essentially independent of size at the critical swimming speed. Estimated aerobic efficiency increased with size at the critical swimming speed, implying that muscle efficiency also increases with size.
This article describes research into the fluid mechanics of fish propulsion, with the ultimate aim of applying the results to ship and submarine propulsion. Simple foils that approximated the swish of a fish tail were constructed in the laboratory. Experiments revealed that the jet vortices in the wake of the flow play a central role in the generation of thrust. By analysing data from the flapping foils, it was found that thrust-induced vortices from optimally when the Strouhal number lay between 0.25 and 0.35. It was found that many fish swing their tails within this optimal range also. From these results, an artificial fish, known as RoboTuna, was constructed. -S.E.Brown
Observations of position holding by brook trout (Salvelinus fontinalis) in a stream channel indicate that they choose specific locations probably related to flow patterns around bottom obstructions. Bilateral denervation of the posterior lateral line system of trout has no effect on their ability to entrain on objects placed in flowing water, providing sufficient visual cues are available. Unilateral ablation resulted in a lateral bias in swimming position relative to the flow obstruction even when visual cues were present. Bilateral denervation of the posterior line system reduced the degree to which trout could entrain on objects when visual cues were omitted. It is suggested that in stream-dwelling fish, such as the brook trout, the lateral line may serve as a detector of flow or pressure discontinuities, enabling the fish to maintain position with minimum expenditure of energy.
In an ongoing research project an autonomous underwater vehicle is to be built that will detect, localize, and avoid objects by means of a fully passive sensory system. Using hot-wire anemometry it measures local water velocities at the vehicle’s hull and thus mimics the lateral-line system of fish and many amphibians. Fish often use the lateral-line system as their
only means for navigation, especially under poor visual conditions. Simulations and theoretical
calculations of the flow around an underwater vehicle show that velocity measurements with
hot-wire anemometers enable an underwater vehicle to detect surfaces, so that no clear sight
or active scanning is necessary for collision avoidance. A first series of experiments validates
theoretical calculations and shows that a vehicle can detect parallel movement to a wall.
The bodies of fish change shape over propulsive, behavioral, developmental, and evolutionary time scales, a general phenomenon that we call "reconfiguration". Undulatory, postural, and form-reconfiguration can be distinguished, studied independently, and examined in terms of mechanical interactions and evolutionary importance. Using a combination of live, swimming fishes and digital robotic fish that are autonomous and self-propelled, we examined the functional relation between undulatory and postural reconfiguration in forward swimming, backward swimming, and yaw turning. To probe how postural and form reconfiguration interact, the yaw turning of leopard sharks was examined using morphometric and kinematic analyses. To test how undulatory reconfiguration might evolve, the digital robotic fish were subjected to selection for enhanced performance in a simulated ecology in which each individual had to detect and move towards a food source. In addition to the general issue of reconfiguration, these investigations are united by the fact that the dynamics of undulatory and postural reconfigurations are predicted to be determined, in part, by the structural stiffness of the fish's body. Our method defines undulatory reconfiguration as the combined, point-by-point periodic motion of the body, leaving postural reconfiguration as the combined deviations from undulatory reconfiguration. While undulatory reconfiguration appears to be the sole or primary propulsive driver, postural reconfiguration may contribute to propulsion in hagfish and it is correlated with differences in forward, and backward, swimming in lamprey. Form reconfigures over developmental time in leopard sharks in a manner that is consistent with an allometric scaling theory in which structural stiffness of the body is held constant. However, correlation of a form proxy for structural stiffness of the body suggests that body stiffness may scale in order to limit maximum postural reconfiguration during routine yaw turns. When structural stiffness and undulatory frequency are modeled as determining the tail's undulatory wave speed, both factors evolve under selection for enhanced foraging behavior in the digital fish-like robots. The methods used in making these distinctions between kinds of reconfiguration have broad applicability in fish biology, especially for quantifying complex motor behaviors in the wild and for simulating selection on behavior that leads to directional evolution of functional phenotypes.
Hydrodynamic imaging using the lateral line plays a critical role in fish behavior. To engineer such a biologically inspired sensing system, we developed an artificial lateral line using MEMS (microelectromechanical system) technology and explored its localization capability. Arrays of biomimetic neuromasts constituted an artificial lateral line wrapped around a cylinder. A beamforming algorithm further enabled the artificial lateral line to image real-world hydrodynamic events in a 3D domain. We demonstrate that the artificial lateral line system can accurately localize an artificial dipole source and a natural tail-flicking crayfish under various conditions. The artificial lateral line provides a new sense to man-made underwater vehicles and marine robots so that they can sense like fish.
Presently, there is a need for devices capable of autonomous locomotion in liquid environments. Humanitarian, industrial and defense applications are numerous and include examples such as search and rescue missions, ocean exploration, and de-mining operations. Due to the nature of the environments involved, the required devices must overcome several challenges. The main challenges are related to hardware performance in terms of propulsion efficiency, mechanical robustness, maneuverability, adaptability, stealth and autonomy. Current traditional approaches that use propeller driven devices have limited success in addressing these challenges. As a result devices that mimic fish-like swimming techniques have emerged as a promising alternative that can provide additional maneuvering features and the promise of improved performance. However, the inherent problems of current biomimetic devices have been identified as: (i) mechanical complexity due to the use of discrete and rigid components, and (ii) lack of a systematic design approach. These problems limit the practical implementation of biomimetic techniques in real mission environments. This thesis presents an alternative approach for implementing biomimetic fish-like swimming techniques by exploiting natural dynamics of compliant bodies.
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2000. Includes bibliographical references (p. 75-76). by John Muir Kumph. S.M.
We present experimental force and power measurements demonstrating that the power required to propel an actively swimming, streamlined, fish-like body is significantly smaller than the power needed to tow the body straight and rigid at the same speed U. The data have been obtained through accurate force and motion measurements on a laboratory fish-like robotic mechanism, 1:2m long, covered with a flexible skin and equipped with a tail fin, at Reynolds numbers up to 10^6, with turbulence stimulation. The lateral motion of the body is in the form of a travelling wave with wavelength lambda and varying amplitude along the length, smoothly increasing from the front to the tail end. A parametric investigation shows sensitivity of drag reduction to the non-dimensional frequency (Strouhal number), amplitude of body oscillation and wavelength lambda, and angle of attack and phase angle of the tail fin. A necessary condition for drag reduction is that the phase speed of the body wave be greater than the forward speed U. Power estimates using an inviscid numerical scheme compare favourably with the experimental data. The method employs a boundary-integral method for arbitrary flexible body geometry and motions, while the wake shed from the fish-like form is modelled by an evolving desingularized dipole sheet.
Online trajectory generation for robots with multiple degrees of freedom is still a difficult and unsolved problem, in particular for non-steady state locomotion, that is, when the robot has to move in a complex environment with continuous variations of the speed, direction, and type of locomotor behavior. In this article we address the problem of controlling the non-steady state swimming and crawling of a novel fish robot. For this, we have designed a control architecture based on a central pattern generator (CPG) implemented as a system of coupled nonlinear oscillators. The CPG, like its biological counterpart, can produce coordinated patterns of rhythmic activity while being modulated by simple control parameters.
To test our controller, we designed BoxyBot, a simple fish robot with three actuated fins capable of swimming in water and crawling on firm ground. Using the CPG model, the robot is capable of performing and switching between a variety of different locomotor behaviors such as swimming forwards, swimming backwards, turning, rolling, moving upwards/downwards, and crawling. These behaviors are triggered and modulated by sensory input provided by light, water, and touch sensors. Results are presented demonstrating the agility of the robot and interesting properties of a CPG-based control approach such as stability of the rhythmic patterns due to limit cycle behavior, and the production of smooth trajectories despite abrupt changes of control parameters.
The robot is currently used in a temporary 20-month long exhibition at the EPFL. We present the hardware setup that was designed for the exhibition, and the type of interactions with the control system that allow visitors to influence the behavior of the robot. The exhibition is useful to test the robustness of the robot for long term use, and to demonstrate the suitability of the CPG-based approach for interactive control with a human in the loop.
This article is an extended version of an article presented at BioRob2006 the first IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics.
The lateral-line system is a unique mechanosensory facility of aquatic animals that enables them not only to localize prey, predator, obstacles, and conspecifics, but also to recognize hydrodynamic objects. Here we present an explicit model explaining how aquatic animals such as fish can distinguish differently shaped submerged moving objects. Our model is based on the hydrodynamic multipole expansion and uses the unambiguous set of multipole components to identify the corresponding object. Furthermore, we show that within the natural range of one fish length the velocity field contains far more information than that due to a dipole. Finally, the model we present is easy to implement both neuronally and technically, and agrees well with available neuronal, physiological, and behavioral data on the lateral-line system.
We have developed an experimental procedure in which the in situ locomotor muscles of dead fishes can be electrically stimulated to generate swimming motions. This procedure gives the experimenter control of muscle activation and the mechanical properties of the body. Using pumpkinseed sunfish, Lepomis gibbosus, we investigated the mechanics of undulatory swimming by comparing the swimming kinematics of live sunfish with the kinematics of dead sunfish made to swim using electrical stimulation. In electrically stimulated sunfish, undulatory waves can be produced by alternating leftright contractions of either all the axial muscle or just the precaudal axial muscle. As judged by changes in swimming speed, most of the locomotor power is generated precaudally and transmitted to the caudal fin by way of the skin and axial skeleton. The form of the traveling undulatory wave as measured by tail-beat amplitude, propulsive wavelength and maximal caudal curvature can be modulated by experimental control of the body's passive stiffness, which is a property of the skin, connective tissue and axial skeleton.
The purpose of this study was to investigate the mechanical control of speed in steady undulatory swimming. The roles of body flexural stiffness, driving frequency and driving amplitude were examined; these variables were chosen because of their importance in vibration theory and their hypothesized functions in undulatory swimming. Using a mold of a pumpkinseed sunfish Lepomis gibbosus, we cast three-dimensional vinyl models of four different flexural stiffnesses. We swam the models in a flow tank and powered them via the input of an oscillating sinusoidal bending couple in the horizontal plane at the posterior margin of the neurocranium. To simulate the hydrodynamic conditions of steady swimming, drag and thrust acting on the model were balanced by adjusting flow speed. Under these conditions, the actuated models generated traveling waves of bending. At steady speeds, the motions of the ventral and lateral surfaces of the model were video-taped and analyzed to yield the following response variables: tail-beat amplitude, propulsive wavelength, wave speed and depth of the trailing edge of the caudal fin. Experimental results showed that changes in body flexural stiffness can control propulsive wavelength, wave speed, Froude efficiency and, in consequence, swimming speed. Driving frequency can control tail-beat amplitude, propulsive wavelength, Froude efficiency, relative rate of working and, in consequence, swimming speed. Although there is no significant correlation between rostral amplitude and swimming speed, rostral amplitude can control swimming speed indirectly by controlling tail-beat amplitude and relative power. Compared with live sunfish using undulatory waves at the same speed, models have a lower Froude efficiency. On the basis of the mechanical control of swimming speed in model sunfish, we predict that, in order to swim at fast speeds, live sunfish increase the flexural stiffness of their bodies by a factor of two relative to their passive body stiffness.
This paper is concerned with the design of a robotic fish and its motion control algorithms. A radio-controlled, four-link biomimetic robotic fish is developed using a flexible posterior body and an oscillating foil as a propeller. The swimming speed of the robotic fish is adjusted by modulating joint's oscillating frequency, and its orientation is tuned by different joint's deflections. Since the motion control of a robotic fish involves both hydrodynamics of the fluid environment and dynamics of the robot, it is very difficult to establish a precise mathematical model employing purely analytical methods. Therefore, the fish's motion control task is decomposed into two control systems. The online speed control implements a hybrid control strategy and a proportional-integral-derivative (PID) control algorithm. The orientation control system is based on a fuzzy logic controller. In our experiments, a point-to-point (PTP) control algorithm is implemented and an overhead vision system is adopted to provide real-time visual feedback. The experimental results confirm the effectiveness of the proposed algorithms.
In the present review, signal-processing capabilities of the canal lateral line organ imposed by its peripheral architecture are quantified in terms of a limited set of measurable physical parameters. It is demonstrated that cupulae in the lateral line canal organ can only partly be described as canal fluid velocity detectors. Deviation from velocity detection may result from resonance, and can be characterized by the extent to which a single dimensionless resonance number, N ( r ), exceeds 1. This number depends on four physical parameters: it is proportional to cupular size, cupular sliding stiffness and canal fluid density, and inversely proportional to the square of fluid viscosity. Situated in a canal, a cupula may benefit from its resonance by compensating for the limited frequency range of water motion that is efficiently transferred into the lateral line canal. The peripheral transfer of hydrodynamic signals, via canal and cupula, leads to a nearly constant sensitivity to outside water acceleration in a bandwidth that ranges from d.c. to a cut-off frequency of up to several hundreds of Hertz, significantly exceeding the cut-off frequency of the lateral line canal. Threshold values of hydrodynamic detection by the canal lateral line organ are derived in terms of water displacement, water velocity, water acceleration and water pressure gradients and are shown to be close to the detection limits imposed by hair cell mechano-transduction in combination with the physical constraints of peripheral lateral line signal transfer. The notion that the combination of canal- and cupular hydrodynamics effectively provides the lateral line canal organ with a constant sensitivity to water acceleration at low frequencies so that it consequently functions as a low-pass detector of pressure gradients, supports the appropriateness of describing it as a sense organ that "feels at a distance" (Dijkgraaf in Biol Rev 38:51-105, 1963).
Fish acquire information about their aquatic environment by means of their mechanosensory lateral-line system. This system consists of superficial and canal neuromasts that sense perturbations in the water surrounding them. Based on a hydrodynamic model presented here, we propose a mechanism through which fish can localize the source of these perturbations. In doing so we include the curvature of the fish body, a realistic lateral line canal inter-pore distance for the lateral-line canals, and the surface boundary layer. Using our model to explore receptor behavior based on experimental data of responses to dipole stimuli we suggest that superficial and canal neuromasts employ the same mechanism, hence provide the same type of input to the central nervous system. The analytical predictions agree well with spiking responses recorded experimentally from primary lateral-line nerve fibers. From this, and taking into account the central organization of the lateral-line system, we present a simple biophysical model for determining the distance to a source.
We report current developments in biomimetic flow-sensors based on mechanoreceptive sensory hairs of crickets. These filiform hairs are highly perceptive to low-frequency sound with energy sensitivities close to thermal threshold. In this work we describe hair-sensors fabricated by a combination of sacrificial poly-silicon technology, to form silicon-nitride suspended membranes, and SU8 polymer processing for fabrication of hairs with diameters of about 50 mum and up to 1 mm length. The membranes have thin chromium electrodes on top forming variable capacitors with the substrate allowing for capacitive read-out. Previously these sensors have been shown to exhibit acoustic sensitivity. Based on a hydrodynamic - mechanical interaction model we derive a figure of merit. We present optical measurements on acoustically excited hair-sensors. Experimental data and the derived models are shown to exhibit good correspondence.
Several physico-mechanical designs evolved in fish are currently
inspiring robotic devices for propulsion and maneuvering purposes in
underwater vehicles. Considering the potential benefits involved, this
paper presents an overview of the swimming mechanisms employed by fish.
The motivation is to provide a relevant and useful introduction to the
existing literature for engineers with an interest in the emerging area
of aquatic biomechanisms. The fish swimming types are presented,
following the well-established classification scheme and nomenclature
originally proposed by Breder. Fish swim either by body and/or caudal
fin (BCF) movements or using median and/or paired fin (MPF) propulsion.
The latter is generally employed at slow speeds, offering greater
maneuverability and better propulsive efficiency, while BCF movements
can achieve greater thrust and accelerations. For both BCF and MPF
locomotion, specific swimming modes are identified, based on the
propulsor and the type of movements (oscillatory or undulatory) employed
for thrust generation. Along with general descriptions and kinematic
data, the analytical approaches developed to study each swimming mode
are also introduced. Particular reference is made to lunate tail
propulsion, undulating fins, and labriform (oscillatory pectoral fin)
swimming mechanisms, identified as having the greatest potential for
exploitation in artificial systems
In an ongoing research project an autonomous underwater vehicle is to be built that will detect, localize, and avoid objects by means of a fully passive sensory system. Using hot-wire anemometry it measures local water velocities at the vehicle's hull and thus mimics the lateral-line system of fish and many amphibians. Fish often use the lateral-line system as their only means for navigation, especially under poor visual conditions. Simulations and theoretical calculations of the flow around an underwater vehicle show that velocity measurements with hot-wire anemometers enable an underwater vehicle to detect surfaces, so that no clear sight or active scanning is necessary for collision avoidance. A first series of experiments validates theoretical calculations and shows that a vehicle can detect parallel movement to a wall.
Fishes have an impressive complement of hydrodynamic and acoustic sensors, commonly referred to as the lateral-line and inner-ear sense organs. The basic receptor elements are the hair cells, which detect the minute displacements imparted to their apical ciliary bundles (Fig. 4.1a). The directional sensitivity of the individual receptor cells is indicated by the asymmetric position of the single kinocilium relative to the several rows of stereocilia. Morphologically, the hair cells of the various sensory clusters are strikingly uniform. Their diversity in function is determined mainly by the peripheral structures coupling the ciliary bundles to the physical world that the animals inhabit.
1. An apparatus is described in which it is possible to study and record the continuous swimming of fish at speeds up to 20 m.p.h.
2. Records made of the swimming at different speeds of dace, trout and goldfish measuring up to 30 cm. in length are reproduced.
3. Speed at any particular frequency of tail beat is shown to be directly related to the length of the specimen, measured from the tip of the snout to the most posterior extremity of the tail.
4. Above a frequency of 5 tail beats per second speed is directly dependent upon frequency up to the maximum values recorded. The results for all sizes and species recorded may be adequately expressed by the formula V = ¼{L(3f - 4)}, where V is the speed in cm. per sec., f is the frequency in beats per sec. and L is the body length in cm.
5. The distance travelled per beat (and hence the speed) is directly dependent upon the amplitude of the tail beat.
6. The amplitude increases with increasing frequency up to a maximum reached at about beats per second. This maximum amplitude is the same for all fish tested and is about one-fifth of the body length.
7. The maximum frequency attainable decreases with increasing size of the specimen. This decrease is slight in the trout and more pronounced in the dace and goldfish. Estimation of the possible maximum frequencies of much bigger fish allows for prediction of the maximum speeds they may be able to attain. Such predicted speeds are in accord with the few measurements that have been made and are of the order of 10 body lengths per second up to a size of 1 m.
Underwater flow sensing is important for many robotics and military applications, including underwater robots and vessels. We report the development of micromachined, distributed flow sensors based on a biological inspiration, the fish lateral line sensors. Design and fabrication processes for realizing individual lateral line sensor nodes are discussed in this paper, along with preliminary characterization results.
Over the past 20 years, experimental analyses of the biomechanics of locomotion in fishes have generated a number of key findings
that are relevant to the construction of biomimetic fish robots. In this paper, we present 16 results from recent experimental
research on the mechanics, kinematics, fluid dynamics, and control of fish locomotion that summarize recent work on fish biomechanics.
The findings and principles that have emerged from biomechanical studies of fish locomotion provide important insights into
the functional design of fishes and suggest specific design features relevant to construction of robotic fish-inspired vehicles
that underlie the high locomotor performance exhibited by fishes.
This paper presents a novel mechatronics design for a 3D swimming robotic fish, namely MT1 (Mechanical Tail) robotic fish. It has a novel tail structure which uses only one motor to generate fish-like swimming motion using C-bends tail shapes. This design enables MT1 to become the first small size robotic fish (<0.5m in length) and be able to dive over 3 meters deep in water. An effective control method with only 5 parameters is proposed to control its 3D swimming behaviours. Experimental results are presented to show the feasibility and good performance of the proposed control algorithms.
Within the broader scope of underwater biomimetics, in this paper we address the relevance of factors such as shape and elasticity distribution in the ability of a compliant device to imitate the kinematic behaviour of a fish. We assess the viability of myometry as a tool to determine candidate mechanical parameters without relying solely on analytical models; we show that we can obtain elasticity distributions that are both consistent with previous theoretical investigations and experimentally better adherent to the passive kinematics of a biological embodiment (rainbow trout).
Although much is now known about the mechanisms that insects, birds and mammals use to orient within familiar areas, our knowledge of such mechanisms in fish is scant. I used the transformational approach to test whether the blind Mexican cave fish can encode shape and size in an internal representation of space. These fish are excellent study animals, as they swim at high velocities (presumably to enhance lateral line organ stimulation) when faced with unfamiliar landmarks or environments. As they are blind, potentially confounding cues from visual global landmarks are unavailable. The fish learnt a square configuration of four landmarks and so must have been be able to encode spatial relationships between the elements within this configuration. After learning landmark arrays, the cave fish showed significant dishabituation (swimming velocity was increased) when exposed to landmark transformations. The fish must therefore have been comparing the environment that they perceived with an internal representation of the environment that they had learnt. The results show that blind Mexican cave fish can encode size (absolute distance between landmarks) and possibly also shape within their spatial maps.
The Draper Laboratory Vorticity Control Unmanned Undersea Vehicle (VCUUV) is the first mission-scale, autonomous underwater
vehicle that uses vorticity control propulsion and maneuvering. Built as a research platform with which to study the energetics
and maneuvering performance of fish-swimming propulsion, the VCUUV is a self-contained free swimming research vehicle which
follows the morphology and kinematics of a yellowfin tuna. The forward half of the vehicle is comprised of a rigid hull which
houses batteries, electronics, ballast and hydraulic power unit. The aft section is a freely flooded articulated robot tail
which is terminated with a lunate caudal fin. Utilizing experimentally optimized body and tail kinematics from the MIT RoboTuna, the VCUUV has demonstrated stable steady swimming speeds up to 1.2 m/sec and aggressive maneuvering trajectories with turning
rates up to 75 degrees per second. This paper summarizes the vehicle maneuvering and stability performance observed in field
trials and compares the results to predicted performance using theoretical and empirical techniques.
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1996. Includes bibliographical references (leaves 183-186).
Considers the design of motion control algorithms for robot fish. We present modeling, control design, and experimental trajectory tracking results for an experimental planar robotic fish system that is propelled using carangiform-like locomotion. Our model for the fish's propulsion is based on quasi-steady fluid flow. Using this model, we propose gaits for forward and turning trajectories and analyze system response under such control strategies. Our models and predictions are verified by experiment.
The bodies and brains of fish have evolved to achieve control objectives beyond the capabilities of current underwater vehicles. One route toward designing underwater vehicles with similar capabilities is to better understand fish physiological design and control strategies. This paper has two objectives: 1) to review clues to artificial swimmer design taken from fish physiology and 2) to formalize and review the control problems that must be solved by a robot fish. The goal is to exploit fish locomotion principles to address the truly difficult control challenges of station keeping under large perturbations, rapid maneuvering, power-efficient endurance swimming, and trajectory planning and tracking. The design and control of biomimetic swimming machines meeting these challenges will require state-of-the-art engineering and biology.
The mechanism of locomotion of aquatic animals can provide us with
new insight into the maneuverability and stabilization of underwater
robots. This paper focuses on biomimesis in the maneuvering performance
of aquatic animals to develop a new device for maneuvering underwater
robots. In this paper, guidance and control in the horizontal plane of a
fish robot equipped with a pair of two-motor-driven mechanical pectoral
fins on both sides of the robot in water currents is presented. The fish
robot demonstrates high performance in terms of maneuverability in such
activities as lateral swimming. The use of fuzzy control enables the
fish robot to perform rendezvous and docking with an underwater post in
water currents
Hydrodynamic and acoustic field detection Sensory Biology of Aquatic Animals
- A J Kalmijin
A. J. Kalmijin, Hydrodynamic and acoustic field detection, Sensory Biology of Aquatic Animals, ed. J. Atema, R. R. Fay, A. N. Popper and W. N. Tavolga, New York, Springer, 83-130, 1988.
Role of the lateral line in fish behaviour, in " Behavior of Teleost Fishes
- H Bleckmann
H. Bleckmann, Role of the lateral line in fish behaviour, in " Behavior of Teleost Fishes, " Chapter 7, pp. 201 – 235, T. J. Pitcher Ed., Chapman and Hall, 1993
Design of a compliant underwater propulsion mechanism by investigating and mimicking the body of a rainbow trout (Oncorhynchus mykiss)
- Taavi Salumäe
Hydrodynamic and acoustic field detection
- A J Kalmijin
- J Atema
- R R Fay
- A N Popper
- W N Tavolga