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Energy Harvesting in Soft Robot Locomotion with Complex Dynamics
Abstract
There has been a lot work in the last decade examining the locomotion principles and properties of mobile soft robots. In terms of energy efficiency, it has also been found that most mobile soft robots reported in the literatures are still in need of improvement. Along the direction, a possible approach to increase the energy efficiency is through the ability to harvest the energy used during the locomotion. The main goal of the paper is to investigate the most important principles to harvest energy in soft robot locomotion with complex and rich dynamics. By observing the energy harvesting ability in a vibration induced soft locomotion with complex dynamics, it is found that the ability to harvest higher voltages does not necessarily lead to a higher energy efficiency. Instead, the ability to harvest a proper amount of voltages at a suitable moment is shown to be more important. These primary findings pave the way of maximizing energy efficiency in soft robot locomotion through energy harvesting.
... Thanks to the development of new low power demanding electronics, such as wireless transceivers and power management electronics specifically designed for energy harvesting applications, new autonomous measurement systems, for use as standalone devices or nodes of a distributed wireless sensor network, are being developed. Such solutions are of high interest in many fields, including robotics, where it could allow to power sensor nodes by scavenging energy from the environment, such as vibrations during locomotion, temperature gradient, or other sources [1][2][3], instead of using external batteries. ...
This paper, for the first time, investigates the possibility of exploiting a nonlinear bistable snap-through buckling structure employing piezoelectric transducers, to implement an autonomous sensor of mechanical vibrations, with an embedded energy harvesting functionality. The device is operated in the presence of noisy vibrations superimposed on a subthreshold deterministic (sinusoidal) input signal. While the capability of the device to harvest a significant amount of energy has been demonstrated in previous works, here, we focus on the signal processing methodology aimed to extract from the sensor output the information about the noise level (in terms of the standard deviation) and the root mean square amplitude of the deterministic component. The developed methodology, supported by experimental evidence, removes the contribution to the overall piezoelectric output voltage ascribable to the deterministic component using a thresholding and windowing algorithm. The contribution to the output voltage due to the noise can be used to unambiguously estimate the noise level. Moreover, an analytical model to estimate, from the measurement of the output voltage, the RMS amplitude of the deterministic input and the noise-related component is proposed.
Battery-less wireless sensor networks (BL-WSNs) are an interesting and sustainable solution for Internet-of-Things (IoT) applications. The sensor nodes in the BL-WSNs are often powered by an energy harvester. Generally, these harvesters provide intermittent energy to the BL-WSNs. Hence, to cater to a variety of applications, the energy harvesters should work as a high-pass filter, that is, provide continuous energy to the BLWSNs. This article proposes a novel design to harvest vibration energy using a coupled Dovetail-shaped piezoelectric and electromagnetic energy harvester (Dovetail-PEM-EH). Unlike earlier PEM-EH designs with either one or two vertical cantilevers, Dovetail-PEM-EH uses three bimorphs and one copper (fixed tip end) cantilever with magnets on the tips. Placing more than two cantilevers with tip magnets requires optimizing distances among cantilevers and selecting tip magnets in such a way that energy harvesting is increased and the design is stable, that is, cantilevers do not collide with each other. A low-complexity binary search-based algorithm is presented to achieve the same. By doing so, the magnetic attractive forces increase the vibration sensitivity of the proposed design, and it works as a high-pass mechanical filter with a low cutoff frequency. The detailed simulation analysis performed in COMSOL shows that there is a minimum
$2\times $
increase in the voltage and six out of the nine tested models show more than
$3\times $
improvement in the harvested power when compared to the state-of-the-art. The hardware implementation of one of the models validates the simulation results with a slight variation.
Soft materials are increasingly utilized for various purposes in many engineering applications. These materials have been shown to perform a number of functions that were previously difficult to implement using rigid materials. Here, we argue that the diverse dynamics generated by actuating soft materials can be effectively used for machine learning purposes. This is demonstrated using a soft silicone arm through a technique of multiplexing, which enables the rich transient dynamics of the soft materials to be fully exploited as a computational resource. The computational performance of the soft silicone arm is examined through two standard benchmark tasks. Results show that the soft arm compares well to or even outperforms conventional machine learning techniques under multiple conditions. We then demonstrate that this system can be used for the sensory time series prediction problem for the soft arm itself, which suggests its immediate applicability to a real-world machine learning problem. Our approach, on the one hand, represents a radical departure from traditional computational methods, whereas on the other hand, it fits nicely into a more general perspective of computation by way of exploiting the properties of physical materials in the real world.
Soft robotics and its related technologies enable robot abilities in several robotics domains including, but not exclusively related to, manipulation, manufacturing, human–robot interaction and locomotion. Although field applications have emerged for soft manipulation and human–robot interaction, mobile soft robots appear to remain in the research stage, involving the somehow conflictual goals of having a deformable body and exerting forces on the environment to achieve locomotion. This paper aims to provide a reference guide for researchers approaching mobile soft robotics, to describe the underlying principles of soft robot locomotion with its pros and cons, and to envisage applications and further developments for mobile soft robotics.
Bouncing locomotion is used frequently in the animal kingdom for high-speed movement over land. Animals also change their stiffness and shape to improve their locomotion ability. Both bouncing movement and stiffness- and shape-changing capabilities have been recently explored in robotics. In this article, a novel soft locomotion robot, VibroBot, is presented, capable of moving using a bouncing gait by inducing whole-body oscillations through rotation of an internal out-of-balance mass. VibroBot is capable of changing both its stiffness and its shape to tackle challenging terrain and to overcome obstacles. When the robot is stiff, it is capable of high-frequency oscillatory locomotion suited to movement on hard surfaces. While in a compliant state, it uses a lower-frequency higher-amplitude hopping gait suitable for traveling over soft or loose ground. Forward speeds of 8.5 cm/s (0.34 body lengths/second) on hard floor in VibroBot’s stiff state and 5 cm/s (0.2 body lengths/second) on sand in its compliant state were recorded. VibroBot can also selectively change its shape to climb obstacles with heights up to 3 cm (20% of the robot’s height in its stiff state), far greater than its hopping apex height (1 cm). Both simple bouncing gaits and stiffness- and shape-changing abilities show great promise for improving the locomotion abilities of soft robots.
Conventionally, engineers have employed rigid materials to fabricate precise, predictable robotic systems, which are easily modelled as rigid members connected at discrete joints. Natural systems, however, often match or exceed the performance of robotic systems with deformable bodies. Cephalopods, for example, achieve amazing feats of manipulation and locomotion without a skeleton; even vertebrates such as humans achieve dynamic gaits by storing elastic energy in their compliant bones and soft tissues. Inspired by nature, engineers have begun to explore the design and control of soft-bodied robots composed of compliant materials. This Review discusses recent developments in the emerging field of soft robotics.
One of the most significant challenges in bio-inspired robotics is how to realize and take advantage of multimodal locomotion, which may help robots perform a variety of tasks adaptively in different environments. In order to address the challenge properly, it is important to notice that locomotion dynamics are the result of interactions between a particular internal control structure, the mechanical dynamics and the environment. From this perspective, this paper presents an approach to enable a robot to take advantage of its multiple locomotion modes by coupling the mechanical dynamics of the robot with an internal control structure known as an attractor selection model. The robot used is a curved-beam hopping robot; this robot, despite its simple actuation method, possesses rich and complex mechanical dynamics that are dependent on its interactions with the environment. Through dynamical coupling, we will show how this robot performs goal-directed locomotion by gracefully shifting between different locomotion modes regulated by sensory input, the robot’s mechanical dynamics and an internally generated perturbation. The efficacy of the approach is validated and discussed based on the simulation and on real-world experiments.
The remarkable advances of robotics in the last 50 years, which represent an incredible wealth of knowledge, are based on the fundamental assumption that robots are chains of rigid links. The use of soft materials in robotics, driven not only by new scientific paradigms (biomimetics, morphological computation, and others), but also by many applications (biomedical, service, rescue robots, and many more), is going to overcome these basic assumptions and makes the well-known theories and techniques poorly applicable, opening new perspectives for robot design and control. The current examples of soft robots represent a variety of solutions for actuation and control. Though very first steps, they have the potential for a radical technological change. Soft robotics is not just a new direction of technological development, but a novel approach to robotics, unhinging its fundamentals, with the potential to produce a new generation of robots, in the support of humans in our natural environments.
This paper presents the complete development and analysis of a soft robotic platform that exhibits peristaltic locomotion. The design principle is based on the antagonistic arrangement of circular and longitudinal muscle groups of Oligochaetes. Sequential antagonistic motion is achieved in a flexible braided mesh-tube structure using a nickel titanium (NiTi) coil actuators wrapped in a spiral pattern around the circumference. An enhanced theoretical model of the NiTi coil spring describes the combination of martensite deformation and spring elasticity as a function of geometry. A numerical model of the mesh structures reveals how peristaltic actuation induces robust locomotion and details the deformation by the contraction of circumferential NiTi actuators. Several peristaltic locomotion modes are modeled, tested, and compared on the basis of speed. Utilizing additional NiTi coils placed longitudinally, steering capabilities are incorporated. Proprioceptive potentiometers sense segment contraction, which enables the development of closed-loop controllers. Several appropriate control algorithms are designed and experimentally compared based on locomotion speed and energy consumption. The entire mechanical structure is made of flexible mesh materials and can withstand significant external impact during operation. This approach allows a completely soft robotic platform by employing a flexible control unit and energy sources.
Scientists are exploring elastic and soft forms of robots, electronic skin and energy harvesters, dreaming to mimic nature and to enable novel applications in wide fields, from consumer and mobile appliances to biomedical systems, sports and healthcare. All conceivable classes of materials with a wide range of mechanical, physical and chemical properties are employed, from liquids and gels to organic and inorganic solids. Functionalities never seen before are achieved. In this review we discuss soft robots which allow actuation with several degrees of freedom. We show that different actuation mechanisms lead to similar actuators, capable of complex and smooth movements in 3d space. We introduce latest research examples in sensor skin development and discuss ultraflexible electronic circuits, light emitting diodes and solar cells as examples. Additional functionalities of sensor skin, such as visual sensors inspired by animal eyes, camouflage, self-cleaning and healing and on-skin energy storage and generation are briefly reviewed. Finally, we discuss a paradigm change in energy harvesting, away from hard energy generators to soft ones based on dielectric elastomers. Such systems are shown to work with high energy of conversion, making them potentially interesting for harvesting mechanical energy from human gait, winds and ocean waves.
Swimmers in nature use body undulations to generate propulsive and manoeuvring forces. The anguilliform kinematics is driven by muscular actions all along the body, involving a complex temporal and spatial coordination of all the local actuations. Such swimming kinematics can be reproduced artificially, in a simpler way, by using the elasticity of the body passively. Here, we present experiments on self-propelled elastic swimmers at a free surface in the inertial regime. By addressing the fluid-structure interaction problem of anguilliform swimming, we show that our artificial swimmers are well described by coupling a beam theory with the potential flow model of Lighthill. In particular, we show that the propagative nature of the elastic wave producing the propulsive force is strongly dependent on the dissipation of energy along the body of the swimmer.
A soft, mobile, morphing robot is a desirable platform for traversing rough terrain and navigating into small holes. In this work, a new paradigm in soft robots is presented that utilizes jamming of a granular medium. The concept of activators (as opposed to actuators) is presented to jam and unjam cells that then modulate the direction and amount of work done by a single central actuator. A prototype jamming soft robot utilizing JSEL (Jamming Skin Enabled Locomotion) with external power and control is discussed and both morphing results and mobility (rolling) results are presented. Future directions for the design of a soft, hole traversing robot are discussed, as is the role and promises of jamming as an enabling technology for soft robotics.
This manuscript describes a unique class of locomotive robot: A soft robot, composed exclusively of soft materials (elastomeric polymers), which is inspired by animals (e.g., squid, starfish, worms) that do not have hard internal skeletons. Soft lithography was used to fabricate a pneumatically actuated robot capable of sophisticated locomotion (e.g., fluid movement of limbs and multiple gaits). This robot is quadrupedal; it uses no sensors, only five actuators, and a simple pneumatic valving system that operates at low pressures (< 10 psi). A combination of crawling and undulation gaits allowed this robot to navigate a difficult obstacle. This demonstration illustrates an advantage of soft robotics: They are systems in which simple types of actuation produce complex motion.
There has been a boost of research activities in robotics using soft materials in the past ten years. It is expected that the use and control of soft materials can help realize robotic systems that are safer, cheaper, and more adaptable than the level that the conventional rigid-material robots can achieve. Contrary to a number of existing review and position papers on soft-material robotics, which mostly present case studies and/or discuss trends and challenges, the review focuses on the fundamentals of the research field. First, it gives a definition of softmaterial robotics and introduces its history, which dates back to the late 1970s. Second, it provides characterization of soft-materials, actuators and sensing elements. Third, it presents two general approaches to mathematical modelling of kinematics of soft-material robots; that is, piecewise constant curvature approximation and variable curvature approach, as well as their related statics and dynamics. Fourth, it summarizes control methods that have been used for soft-material robots and other continuum robots in both model-based fashion and model-free fashion. Lastly, applications or potential usage of soft-material robots are described related to wearable robots, medical robots, grasping and manipulation.
There has been a boost of research activities in robotics using soft materials in the past ten years. It is hoped that the use and control of soft materials can help realize robotic systems that are safer, cheaper, and more adaptable than the level that the conventional rigid-material robots can achieve. Different from a number of existing review or position papers on soft-material robotics which mostly present case studies and/or discuss trends and challenges, the review focuses on the fundamentals of the research field. First, it gives a definition of soft-material robotics and introduces its history which dates back to the late 1970s. Second, it provides characterization of soft-materials, actuators and sensing elements. Third, it presents two general approaches to mathematical modelling of kinematics of soft-material robots i.e. piecewise constant curvature approximation and variable curvature approach, as well as their related statics and dynamics. Fourth, it summarizes control methods that have been used for soft-material robots and other continuum robots in both model-based fashion and model-free fashion. Lastly, applications or potential usage of soft-material robots are described related to wearable robots, medical robots, grasping and manipulation.
In this paper, we investigate the energy harvesting of a piezoelectric composite in a knee pad during walking motion. We use a humanoid robot as a test bed for the experiments using the knee pad. The humanoid wears the knee pad hosting the piezoelectric composite, and its operating knee motion mimics the walking based on the data captured from a human. The use of the humanoid enables the motion to be completely repeatable. We quantitatively study the energy harvesting by using the repeated motion. An electromechanical model for the piezoelectric energy harvester is used to estimate power transferred to varied load resistances under the repeated knee motion. With a good agreement between the experiments and the model predictions, we demonstrate power harvesting on the order of ten microWatts.
In this article, we propose a new technique which exploits a robot’s (intelligently) controlled mobility to maximise stored radio energy. In particular, we examine a scenario where the mobile robot takes a break from its normal activity for a duration of T secs. This ‘dead time’ consists of three phases
- searching, positioning and resting - which ensure that the robot can optimise its energy harvesting from a base station transmitting a narrowband RF signal over a flat fading wireless channel. We utilise the mobility diversity principle, which arises due to the spatial wireless channel diversity experienced by motion of the robot. By optimal exploitation of the small scale fading we maximize the net amount of energy (i.e., the energy harvested by the robot minus the mechanical energy used for motion) that the robot stores over the ‘dead time’. To the best of the authors’ knowledge, this article is the first use of the mobility diversity principle to optimise energy harvesting from
an RF signal. We demonstrate that mobility, if intelligently controlled, is actually not a foe but is indeed a friend which can provide significant benefits under wireless fading channels.
Through simulations we verify the analytical results and illustrate the improvement in the energy stored compared with not using intelligent mobility. Finally, we show that the efficiency of our
approach is clearly coupled with various design parameters including the centre frequency of the narrowband RF signal and the duration of the ‘dead time’.
Co-robots that can effectively move with and operate alongside humans in a variety of conditions could revolutionize the utility of robots for a wide range of applications. Unfortunately, most current robotic systems have difficulty operating in human environments that people easily traverse, much less interact with people. Wheeled robots have difficulty climbing stairs or going over rough terrain. Heavy and powerful legged robots pose safety risks when interacting with humans. Compliant, lightweight tensegrity robots built from interconnected tensile (cables) and compressive (rods) elements are promising structures for co-robotic applications. This paper describes design and control of a rapidly prototyped tensegrity robot for locomotion. The software and hardware of this robot can be extended to build a wide range of tensegrity robotic configurations and control strategies. This rapid prototyping approach will greatly lower the barrier-of-entry in time and cost for research groups studying tensegrity robots suitable for co-robot applications.
This paper explores a design strategy of hopping robots, which makes use of free vibration of an elastic curved beam. In this strategy, the leg structure consists of a specifically shaped elastic curved beam and a small rotating mass that induces free vibration of the entire robot body. Although we expect to improve energy efficiency of locomotion by exploiting the mechanical dynamics, it is not trivial to take advantage of the coupled dynamics between actuation and mechanical structures for the purpose of locomotion. From this perspective, this paper explains the basic design principles through modeling, simulation, and experiments of a minimalistic hopping robot platform. More specifically, we show how to design elastic curved beams for stable hopping locomotion and the control method by using unconventional actuation. In addition, we also analyze the proposed design strategy in terms of energy efficiency and discuss how it can be applied to the other forms of legged robot locomotion.
Abstract In recent years, there has been increasing interest in the study of gait patterns in both animals and robots, because it allows us to systematically investigate the underlying mechanisms of energetics, dexterity, and autonomy of adaptive systems. In particular, for morphological computation research, the control of dynamic legged robots and their gait transitions provides additional insights into the guiding principles from a synthetic viewpoint for the emergence of sensible self-organizing behaviors in more-degrees-of-freedom systems. This article presents a novel approach to the study of gait patterns, which makes use of the intrinsic mechanical dynamics of robotic systems. Each of the robots consists of a U-shaped elastic beam and exploits free vibration to generate different locomotion patterns. We developed a simplified physics model of these robots, and through experiments in simulation and real-world robotic platforms, we show three distinctive mechanisms for generating different gait patterns in these robots.
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