A distributed MPC framework for road-following formation control of car-like vehicles
Xiangjun Qian, Florent Altché, Arnaud de La Fortelle, Fabien Moutarde · 2016
This work presents a novel framework for the formation control of multiple autonomous ground vehicles in an on-road environment. Unique challenges of this problem lie in 1) the design of collision avoidance strategies with obstacles and with other vehicles in a highly structured environment, 2) dynamic reconfiguration of the formation to handle different task specifications. In this paper, we design a local MPC-based trajectory planner for each individual vehicle to follow a reference trajectory while satisfying the various kinematic and dynamic constraints of the vehicles as well as collision avoidance and formation-keeping requirements. The reference trajectory of a vehicle is computed from its leader's trajectory, based on a predefined formation tree. We use logic rules to organize the collision avoidance behaviors of member vehicles. Moreover, we propose a methodology to safely reconfigure the formation on-the-fly. The proposed framework has been validated using high-fidelity simulations.