T-HTN: Timeline based HTN Planning for Multiple Robots
Published in ICAPS | Hierarchical Planning, 2022
Effective coordinated actions by a team of robots operating in close proximity to one another is an important requirement in many emerging applications, ranging from warehousing and material movement to the conduct of autonomous house-keeping and maintenance of deep space habitats during unmanned periods. Yet, such multi-robot planning problems remain a significant challenge for contemporary planning technologies, due to several complicating factors: goals must be assigned to robots and accomplished over time in the presence of complex temporal and spatial constraints in a manner that optimizes overall team performance, attention must be given to the durational uncertainty inherent in robot task execution, and planning must be responsive to changing and unexpected execution circumstances. In this paper, we present T-HTN, a novel planner that attempts to overcome this challenge by coupling the structure and efficiency of Hierarchical Task Network (HTN) models with the flexible scheduling infrastructure of timeline-based planning systems. We present initial results on a simple set of multi-robot problems that show the potential of T-HTN in comparison to a state-of-the-art PDDL-style temporal planner.