Consensus Algorithm for Obstacle Avoidance and Formation Control

This article proposes a new formulation for walking behavior of a group of autonomous robots that adopts socio-dynamic capabilities of a pedestrian crowd. The socio-dynamic capabilities here mean the ability to receive position information from the other robots, to follow the behavior of the group without compromising its safety. The socio-dynamic behavior which will be implemented in the robot group adopted from the model of human walking behavior in a pedestrian crowd, which is known as Social Force Model (SFM). In this research, factors contained in SFM will be induced into a consensus algorithm and then will be implemented into a group of humanoid robots. The aim of the integration of SFM into consensus algorithm is to create a group of robots that are capable of carrying out its collective tasks while still able to maintain its safety. The attractive feature of the proposed algorithm is the fact that robots are still back to the formation after it avoid obstacle. Simulation and experiment results show the effectiveness of the proposed algorithm. Experiments were performed in this research is the first consensus algorithm implementation on a group of humanoid robot.