Magnenat, StéphaneVoelkle, MartinMondada, Francesco2009-09-052009-09-052009-09-05200910.1007/978-3-642-10817-4_99https://infoscience.epfl.ch/handle/20.500.14299/42447WOS:000279602600099Autonomous 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 (HTN) 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 HTN 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.mobile robotdistributedplanninghtnliftingA*d-buszeroconfavahi[MOBOTS]marxbottext::conference output::conference proceedings::conference paper