This paper presents a framework developed for an industrial robotics system that utilises two different planning components. At a high level, a multi-robot mission planner interfaces with a fleet and environment manager and uses multiagent planning techniques to build mission assignments to be distributed to a robot fleet. On each robot, a task planner automatically converts the robot's world model and skill definitions into a planning problem which is then solved to find a sequence of actions that the robot should perform to complete its mission. This framework is demonstrated on an industrial kitting task in a real-world factory environment.
|Title of host publication||Proceedings of the 27th International Conference on Automated Planning and Scheduling|
|Number of pages||9|
|Publication status||Published - 18 Jun 2017|
|Event||27th International Conference on Automated Planning and Scheduling 2017 - Pittsburgh, United States|
Duration: 18 Jun 2017 → 23 Jun 2017
|Name||International Conference on Automated Planning and Scheduling|
|Conference||27th International Conference on Automated Planning and Scheduling 2017|
|Abbreviated title||ICAPS 2017|
|Period||18/06/17 → 23/06/17|
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- School of Mathematical & Computer Sciences - Professor
- School of Mathematical & Computer Sciences, Computer Science - Professor
Person: Academic (Research & Teaching)