Bioinspiration & Biomimetics · 2023 · 10 citations · 44 references
EngineeringComputer ScienceRobotics EngineeringRobot ControlRoboticsUnderwater RoboticsBio-inspired Swarm DesignEmergent BehaviorFish LocomotionMarine Robot ControlRobot Control ArchitectureSwarm CoordinationBio-inspired Swarm AlgorithmsBioinspired Underwater RoboticsFish-inspired RoboticsFish-inspired RobotsFlockingFlocking ControlSchooling Fish BehaviorStigmergy
This study aims to present a novel flocking algorithm for robotic fish that will aid the study of fish in their natural environment. The algorithm, fish-inspired robotic algorithm (FIRA), amalgamates the standard flocking behaviors of attraction, alignment, and repulsion, together with predator avoidance, foraging, general obstacle avoidance, and wandering. The novelty of the FIRA algorithm is the combination of predictive elements to counteract processing delays from sensors and the addition of memory. Furthermore, FIRA is specifically designed to work with an indirect communication method that leads to superior performance in collision avoidance, exploration, foraging, and the emergence of realistic behaviors. By leveraging a high-latency, non-guaranteed communication methodology inspired by stigmergy methods inherent in nature, FIRA successfully addresses some of the obstacles associated with underwater communication. This breakthrough enables the realization of inexpensive, multi-agent swarms while concurrently harnessing the advantages of tetherless communication. FIRA provides a computational light control algorithm for further research with low-cost, low-computing agents. Eventually, FIRA will be used to assimilate robots into a school of biological fish, to study or influence the school. This study endeavors to demonstrate the effectiveness of FIRA by simulating it using a digital twin of a bio-inspired robotic fish. The simulation incorporates the robot's motion and sensors in a realistic, real-time environment with the algorithm used to direct the movements of individual agents. The performance of FIRA was tested against other collective flocking algorithms to determine its effectiveness. From the experiments, it was determined that FIRA outperformed the other algorithms in both collision avoidance and exploration. These experiments establish FIRA as a viable flocking algorithm to mimic fish behavior in robotics.
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Seyedali Mirjalili, Seyed Mohammad Mirjalili, Seyed Mohammad Mirjalili et al. · Advances in Engineering Software · 2014 · 18.4K citations · Full text
Flocks, herds and schools: A distributed behavioral model
Craig W. Reynolds · 1987 · 7.8K citations
Life Sciences, Biology, Zoology +17
Novel Type of Phase Transition in a System of Self-Driven Particles
Tamás Vicsek, András Czirók, Eshel Ben‐Jacob et al. · Physical Review Letters · 1995 · 7.4K citations · Full text
Tamás Vicsek, Anna Zafeiris · Physics Reports · 2012 · 2.9K citations · Full text