Obstacle avoidance flocking motion in multi-agent systems with limited sensing radius and heterogeneous input constraints
Published in Advanced Robotics, 2022
Recommended citation: Eber Jafet Ávila-Martínez. (2022). "Obstacle avoidance flocking motion in multi-agent systems with limited sensing radius and heterogeneous input constraints" Advanced Robotics.
Abstract: This paper addresses the leaderless and leader-followers flocking motion problems of multi-agent systems in a workspace with obstacles. We consider inertial agents with equally limited communica- tion radius and heterogeneous input constraints. Using the notion of proximity graphs, we provide distributed controllers to induce the desired flocking behaviour. Unlike previous results, our con- troller designs do not require predicted states or a target determination scheme and allow edge deletions. Also, by taking advantage of the group’s heterogeneity, our controllers allow agents with less restrictive input constraints to compensate for the control effort that their less capa- ble neighbours cannot provide. We illustrate the effectiveness of our proposals through numerical simulations.