Hierarchically Consistent Motion Primitives for Quadrotor Coordination

Abstract

We present a hierarchical framework for motion planning of a large collection of agents. The proposed framework starts from low level motion primitives over a gridded workspace and provides a set of rules for constructing higher level motion primitives. Our hierarchical approach is highly scalable and robust making it an ideal tool for planning for multi-agent systems. Results are demonstrated experimentally on a collection of quadrotors that must navigate a cluttered environment while maintaining a formation.

8 pages, 6 figures, video: http://tiny.cc/hier-moprim; submitted to Conference on Decision and Control 2019