Adaptive and Collision-free Line Coverage Algorithm for Multi-agent Networks with Unknown Density Function

This paper studies the coverage control problems for a group of agents on a given line, in which both the unknown density function and the collision avoidance among the agents are taken into consideration. To deal with this problem, a novel adaptive line coverage control algorithm is proposed to deploy the agents. In details, the density function is used to describe the distribution of the interested information over the line. Then, an adaptive estimation algorithm is provided to approximate the density function. Comparing with the other density estimation algorithms, the estimation accuracy and efficiency of our proposed algorithm are improved by using the linear regression techniques and a group of error-correction functions. On this basis, a line coverage control scheme with parameter conditions is provided to deploy the agents without any collision. Moreover, the stability of proposed coverage system is strictly analyzed. In final, both numerical simulations and experiments are provided respectively to validate the proposed approaches.