Collision Recognition and Direction Changes Using Fuzzy Logic for Small Scale Fish Robots by Acceleration Sensor Data.
ABSTRACT 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.
Conference Proceeding: Estimation of sound direction for improved interaction of entertainment dolphin robots[show abstract] [hide abstract]
ABSTRACT: In this paper, in order to improve the entertainment dolphin robotpsilas ability to interact with people, a pair of microphones as the ears of a dolphin robot is used to estimate the peak sound directions from surrounding viewers. Dolphin robots should turn towards people who want to interact with them, while swimming autonomously. A pair of left and right microphones is located to form the binaural ears of a dolphin robot. Since the magnitudes of the measured microphone signals decrease as the difference between directions of the microphone and sounds increases, the magnitudes of the left and right signals of microphones are compared to find the sound direction relative to the robotpsilas body line. The same rule applies to the second pair of microphones to determine the sound direction relative to the front.Consumer Electronics, 2008. ISCE 2008. IEEE International Symposium on; 05/2008
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ABSTRACT: The problems of detection and pattern recognition of obstacles are the most important concerns for fish robots’ path planning to make natural and smooth movements as well as to avoid collision. We can get better control results of fish robot trajectories if we obtain more information in detail about obstacle shapes. The method employing only simple distance measuring IR sensors without cameras and image processing is proposed. The capability of a fish robot to recognize the features of an obstacle to avoid collision is improved using neuro-fuzzy inferences. Approaching angles of the fish robot to an obstacle as well as the evident features such as obstacles’ sizes and shape angles are obtained through neural network training algorithms based on the scanned data. Experimental results show the successful path control of the fish robot without hitting on obstacles.Soft Computing 01/2008; 12:715-720. · 1.12 Impact Factor
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ABSTRACT: We present a sonar localization method using ubiquitous sensor network for autonomous water pollution monitoring fish robots. Autonomous tracking is one of important functions in mobile underwater vehicles which monitor water pollution indices. When fish robots find obstacles on its path, proper direction changes to avoid collision are necessary. Otherwise, they should follow the given tracks as close as possible to obtain a pollution map. For efficient tracking performance and procedures of surveying water areas, fish robots use GPS and a sonar system to find exact localization. Although GPS is a fundamental tool to obtain positional information, it is not the best choice in our system due to large errors. Fish robots need to have more precise localization methods. In this paper, we propose to employ USN motes with sonar system to transmit ultrasonic sound to calculate precise positional information. Our experimental results show that fish robots obtain more detailed positional information and make better tracking performance in the real situation.Signal Processing and Information Technology, 2007 IEEE International Symposium on; 01/2008