Path planning for fast swarm source seeking in unknown environments

This article proposes a novel path planning method for source seeking by UAV swarm using extremum seeking control mechanism and combined artificial potential functions, without the knowledge of position information. In particular, the swarm source seeking problem is reformulated as a minimum seeking of a combined artificial potential function that considers the potentials of obstacles, source, and collision avoidance between UAVs. The explicit form of the combined artificial potential function is unknown and its value can be measured by the sensors mounted on UAVs. The fast extremum seeking mechanism based on the normalized extremum seeking method is exploited to find the gradient of the combined artificial potential function and the target is located without using its position information. Finally, extensive simulations of source seeking for single UAV and swarm are presented to illustrate the effectiveness of the proposed path planning method.