Optimal Sequential Task Assignment and Path Finding for Multi-Agent Robotic Assembly Planning

Kyle Brown1, Oriana Peltzer1, Martin Sehr2, Mac Schwager1, Mykel Kochenderfer1

  • 1Stanford University
  • 2Siemens Corporation

Details

09:45 - 10:00 | Mon 1 Jun | Room T11 | MoA11.3

Session: Path Planning for Multiple Mobile Robots or Agents I

Abstract

We study the problem of sequential task assignment and collision-free routing for large teams of robots in applications with inter-task precedence constraints (e.g., task A and task B must both be completed before task C may begin). Such problems commonly occur in assembly planning for robotic manufacturing applications, in which sub-assemblies must be completed before they can be combined to form the final product. We propose a hierarchical algorithm for computing makespan-optimal solutions to the problem. The algorithm is evaluated on a set of randomly generated problem instances where robots must transport objects between stations in a ``factory'' grid world environment. In addition, we demonstrate in high-fidelity simulation that the output of our algorithm can be used to generate collision-free trajectories for non-holonomic differential-drive robots.