Probabilistic planning is very useful for handling uncertainty in planning tasks to be carried out by robots. ROSPlan is a framework for task planning in the Robot Operating System (ROS), but until now it has not been possible to use probabilistic planners within the framework. This systems paper presents a standardized integration of probabilistic planners into ROSPlan that allows for reasoning with non-deterministic effects and is agnostic to the probabilistic planner used. We instantiate the framework in a system for the case of a mobile robot performing tasks indoors, where probabilistic plans are generated and executed by the PROST planner. We evaluate the effectiveness of the proposed approach in a real-world robotic scenario.
|Name||Lecture Notes in Computer Science|
|Conference||The 20th Towards Autonomous Robotic Systems Conference (TAROS 2019)|
|Abbreviated title||TAROS 2019|
|Period||3/07/19 → 5/07/19|
- probabilistic planning
- task planning