Collaborative Navigation Based on Gene Regulatory Networks and Finite State Machine

In this study, we propose a novel robot navigation algorithm that combines a gene regulatory network (GRN) with a finite state machine (FSM). The GRN provides robots with a concentration field based on coupled target information and local obstacle information within the sensor range. The robots employ FSM mechanism to make behavioral choices according to their actual environment and current state of the other robots. Through mutual communication between the swarm robots, the robot's experience of exploring unknown paths is realized, and the overall navigation efficiency of the robot is maximized. Different task scenarios are designed and the effectiveness of the proposed method is experimentally verified.