An Extended Any-angle Path Planning Algorithm for Maintaining Formation of Multi-agent Jellyfish Elimination Robot System

Abstract

In recent years, the increasing influence of climate change has given rise to an uncontrolled proliferation of jellyfish in marine habitats that has visibly damaged many ecosystems and industries and poses a threat to human life. To resolve this issue, our team developed a robotic system called JEROS (Jellyfish Elimination RObotic Swarm) to successfully and efficiently remove jellyfish. JEROS consists of multiple unmanned surface vehicles that freely move in a marine environment to scavenge for and eliminate jellyfish. For controlling formation of JEROS, the leader-follower scheme is used, but this can be sometimes difficult to apply in an ocean environment. When the follower robots are tracking in accordance with the leader's following route without the performance limitation of the robot being considered, the formation cannot be well maintained even if a formation control algorithm is applied to the robots. Maintaining formation is important for efficiency of the jellyfish removal operation. If the formation cannot be well maintained while the robots are moving, the operation area becomes irregular and consequently, the removal operation entails performing repetitive tasks. Therefore, in this paper, we propose the extended any-angle, named extended ARC (Angular-Rate-Constrained)-Theta* path planning algorithm for maintaining formation of the JEROS system to enhance the efficiency of jellyfish removal. To evaluate the performance of the proposed path planning algorithm, we performed field tests at Bang-dong Reservoir in Daejeon, South Korea