Planner9, a HTN Planner Distributed on Groups of Miniature Mobile Robots

Autonomous mobile robots are promising tools for operations in environments that are difficult to access for humans. When these environments are dynamic and non-deterministic, like in collapsed buildings, the robots must coordinate their actions and the use of resources using planning. This paper presents Planner9, a hierarchical task. network (Firm) planner that runs on groups of miniature mobile robots. These robots have limited computational power and memory, but are well connected through Wi-Fi. Planner9 takes advantage of this connectivity to distribute the planning over different robots. We have adapted the WIN algorithm to perform parallel search using A* and to limit the number of search nodes through lifting. We show that Planner9 scales well with the number of robots, even on non-linear tasks that involve recursions in their decompositions. We show that contrary to JSHOP2, Planner9 finds optimal plans.