Using Metareasoning on a Mobile Ground Robot to Recover from Path Planning Failures

dc.contributor.authorMolnar, Sidney
dc.contributor.authorMueller, Matt
dc.contributor.authorMacpherson, Robert
dc.contributor.authorRhoads, Lawrence
dc.contributor.authorHerrmann, Jeffrey W.
dc.date.accessioned2023-02-16T13:41:25Z
dc.date.available2023-02-16T13:41:25Z
dc.date.issued2023-02
dc.description.abstractAutonomous mobile ground robots use global and local path planners to determine the routes that they should follow to achieve mission goals while avoiding obstacles. Although many path planners have been developed, no single one is best for all situations. This paper describes metareasoning approaches that enable a robot to select a new path planning algorithm when the current planning algorithm cannot find a feasible solution. We implemented the approaches within a ROS-based autonomy stack and conducted simulation experiments to evaluate their performance in multiple scenarios. The results show that these metareasoning approaches reduce the frequency of failures and reduce the time required to complete the mission.en_US
dc.description.sponsorshipThis work was supported by the U.S. Army Research Laboratory (Award W911NF2120076).en_US
dc.identifierhttps://doi.org/10.13016/rf8z-jgnk
dc.identifier.urihttp://hdl.handle.net/1903/29723
dc.language.isoen_USen_US
dc.relation.isAvailableAtInstitute for Systems Researchen_us
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)en_us
dc.subjectmetareasoningen_US
dc.subjectautonomyen_US
dc.subjectpath planningen_US
dc.subjectroboticsen_US
dc.titleUsing Metareasoning on a Mobile Ground Robot to Recover from Path Planning Failuresen_US
dc.typeTechnical Reporten_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Metareasoning_for_the_stack.pdf
Size:
2.35 MB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.57 KB
Format:
Item-specific license agreed upon to submission
Description: