A Framework for Multi-Vehicle Navigation Using Feedback-Based Motion Primitives
It addresses robust multi-agent motion planning for heterogeneous agents, but the approach is incremental, combining existing ideas (motion primitives, automata, shortest path) without clear SOTA improvement.
The paper presents a hybrid control framework for multi-vehicle motion planning using feedback-based motion primitives, demonstrating robust navigation for multiple quadrocopters in 2D/3D workspaces.
We present a hybrid control framework for solving a motion planning problem among a collection of heterogenous agents. The proposed approach utilizes a finite set of low-level motion primitives, each based on a piecewise affine feedback control, to generate complex motions in a gridded workspace. The constraints on allowable sequences of successive motion primitives are formalized through a maneuver automaton. At the higher level, a control policy generated by a shortest path non-deterministic algorithm determines which motion primitive is executed in each box of the gridded workspace. The overall framework yields a highly robust control design on both the low and high levels. We experimentally demonstrate the efficacy and robustness of this framework for multiple quadrocopters maneuvering in a 2D or 3D workspace.