A Modular Framework for Motion Planning using Safe-by-Design Motion Primitives
Vukosavljev, Marijan, Kroeze, Zachary, Schoellig, Angela P., Broucke, Mireille E.
–arXiv.org Artificial Intelligence
We present a modular framework for solving a motion planning problem among a group of robots. The proposed framework utilizes a finite set of low level motion primitives to generate motions in a gridded workspace. The constraints on allowable sequences of motion primitives are formalized through a maneuver automaton. At the high level, a control policy determines which motion primitive is executed in each box of the gridded workspace. We state general conditions on motion primitives to obtain provably correct behavior so that a library of safe-by-design motion primitives can be designed. The overall framework yields a highly robust design by utilizing feedback strategies at both the low and high levels. We provide specific designs for motion primitives and control policies suitable for multi-robot motion planning; the modularity of our approach enables one to independently customize the designs of each of these components. Our approach is experimentally validated on a group of quadrocopters.
arXiv.org Artificial Intelligence
Oct-20-2025
- Country:
- Europe > United Kingdom
- England > Cambridgeshire > Cambridge (0.04)
- North America > Canada
- Europe > United Kingdom
- Genre:
- Research Report (0.50)
- Technology: