Conference Paper

Collision Recognition and Direction Changes Using Fuzzy Logic for Small Scale Fish Robots by Acceleration Sensor Data.

DOI: 10.1007/11540007_41 Conference: Fuzzy Systems and Knowledge Discovery, Second International Conference, FSKD 2005, Changsha, China, August 27-29, 2005, Proceedings, Part II
Source: DBLP


For natural and smooth movement of small scale fish robots, collision detection and direction changes are important. Typical
obstacles are walls, rocks, water plants and other nearby robots for a group of small scale fish robots and submersibles that
have been constructed in our lab. Two of 2-axes acceleration sensors are employed to measure the three components of collision
angles, collision magnitudes, and the angles of robot propulsion. These data are integrated using fuzzy logic to calculate
the amount of propulsion direction changes. Because caudal fin provides the main propulsion for a fish robot, there is a periodic
swinging noise at the head of a robot. This noise provides a random acceleration effect on the measured acceleration data
at the collision instant. We propose an algorithm based on fuzzy logic which shows that the MEMS-type accelerometers are very
effective to provide information for direction changes.

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    • "Particularly, a fishlike underwater robot is one of these categories. Our lab introduced a simple fishlike robot in 2005[3], and has improved and added new functions in various manners[4] [5] [6]. To confirm their effectiveness, our constructed fish robots have been tested in a tank for user interaction as well as collision avoidance, maneuverability, control performance, posture maintenance, path design, and data "
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    ABSTRACT: We present an autonomous entertainment dolphin robot system based on ubiquitous sensor networks(USN). Generally, It is impossible to apply to USN and GPS in underwater bio-mimetic robots. But An Entertainment dolphin robot which presented in this paper operates on the water not underwater. Navigation of the underwater robot in a given area is based on GPS data and the acquired position information from deployed USN motes with emphasis on user interaction. Body structures, sensors and actuators, governing microcontroller boards, and swimming and interaction features are described for a typical entertainment dolphin robot. Actions of mouth-opening, tail splash or water blow through a spout hole are typical responses of interaction when touch sensors on the body detect users' demand. Dolphin robots should turn towards people who demand to interact with them, while swimming autonomously. The functions that are relevant to human-robot interaction as well as robot movement such as path control, obstacle detection and avoidance are managed by microcontrollers on the robot for autonomy. Distance errors are calibrated periodically by the known position data of the deployed USN motes.
    The KIPS Transactions PartA 08/2009; 16A(4):255-262. DOI:10.3745/KIPSTA.2009.16-A.4.255
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    • "It is also well known that fish achieve excellent power efficiency and maneuverability that have advantages over conventional propeller-based marine vehicles[1] [2] [3]. Our lab introduced a simple fishlike robot in 2005[4], and improved and added new functions in various manners[5] [6]. The conventional methods of water pollution monitoring collect data by sensors attached on fixed posts. "
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    ABSTRACT: We introduce an autonomous water pollution monitoring system that searches the sources of water pollution and makes measurements of relevant data using a fish robot. A fish robot searches and monitors various areas using GPS receivers and directional information. A fish robot has three microcontrollers which provide full functions, for example, motor operations for the swimming of a fish robot, analog sensor data acquisition including temperature and infrared distance sensors, decoding GPS information, counting the time of sonar in ultrasound sensors and a directional sensor, collecting information of water pollution measurement sensors from Vernier Labpro, and communications. A fish robot swims autonomously in predefined areas and collects the water pollution indexes. Collected information by a fish robot is sent to data collecting nodes by USN motes and Bluetooth, and the data are accessible on the Internet by Ethernet devices.
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    • "The detectable range is reduced to about 12-30cm underwater, though the range is 10-80cm in the air. The configuration of the sensors on the fish robot's body is shown in Fig 2. Since obstacle avoidance is the most important in mobile robot, whether it is wheel based or not, lots of previous studies have presented a variety of methods and applications [2] [3] [4] [5]. Fig. 2. Sensor configuration on a fish robot "
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    ABSTRACT: Fuzzy decision making on trajectory direction changes of pollution monitoring robots is addressed in this paper. Measured pollution densities and the possible existence of obstacles are used as the two fundamental data. While pursuing water pollution monitoring tasks, underwater robots may experience serious difficulties due to various kinds of obstacles in the water. Therefore, one of the major concerns for underwater robots is to detect and recognize obstacles in advance for natural and smooth movements without collision. Trajectory direction changes of a robot should be made so that the robot can move in the direction that the measured pollution data is increased most, especially when there are no obstacles. When there are obstacles along the robot's path in the polluted area, proper trade-off should be made between the steepest ascending direction of pollutant densities and the possibilities of collision with obstacles or traps in them. Our experimental results show that underwater robots, which change the direction following the proposed fuzzy decision results, make their movement to the area of higher pollution density without collision.
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