Robust online belief space planning in changing environments: Application to physical mobile robots

Handle URI:
http://hdl.handle.net/10754/599525
Title:
Robust online belief space planning in changing environments: Application to physical mobile robots
Authors:
Agha-mohammadi, Ali-akbar; Agarwal, Saurav; Mahadevan, Aditya; Chakravorty, Suman; Tomkins, Daniel; Denny, Jory; Amato, Nancy M.
Abstract:
© 2014 IEEE. Motion planning in belief space (under motion and sensing uncertainty) is a challenging problem due to the computational intractability of its exact solution. The Feedback-based Information RoadMap (FIRM) framework made an important theoretical step toward enabling roadmap-based planning in belief space and provided a computationally tractable version of belief space planning. However, there are still challenges in applying belief space planners to physical systems, such as the discrepancy between computational models and real physical models. In this paper, we propose a dynamic replanning scheme in belief space to address such challenges. Moreover, we present techniques to cope with changes in the environment (e.g., changes in the obstacle map), as well as unforeseen large deviations in the robot's location (e.g., the kidnapped robot problem). We then utilize these techniques to implement the first online replanning scheme in belief space on a physical mobile robot that is robust to changes in the environment and large disturbances. This method demonstrates that belief space planning is a practical tool for robot motion planning.
Citation:
Agha-mohammadi A, Agarwal S, Mahadevan A, Chakravorty S, Tomkins D, et al. (2014) Robust online belief space planning in changing environments: Application to physical mobile robots. 2014 IEEE International Conference on Robotics and Automation (ICRA). Available: http://dx.doi.org/10.1109/ICRA.2014.6906602.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2014 IEEE International Conference on Robotics and Automation (ICRA)
KAUST Grant Number:
KUS-C1-016-04
Issue Date:
May-2014
DOI:
10.1109/ICRA.2014.6906602
Type:
Conference Paper
Sponsors:
This research supported in part by AFOSR GrantFA9550-08-1-0038 and by NSF awards CNS-0551685, CCF-0833199,CCF-0830753, IIS-0916053, IIS-0917266, EFRI-1240483, RI-1217991, byNIH NCI R25 CA090301-11, by Chevron, IBM, Intel, Oracle/Sun and byAward KUS-C1-016-04, made by King Abdullah University of Scienceand Technology (KAUST). J. Denny supported in part by an NSF GraduateResearch Fellowship.
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorAgha-mohammadi, Ali-akbaren
dc.contributor.authorAgarwal, Sauraven
dc.contributor.authorMahadevan, Adityaen
dc.contributor.authorChakravorty, Sumanen
dc.contributor.authorTomkins, Danielen
dc.contributor.authorDenny, Joryen
dc.contributor.authorAmato, Nancy M.en
dc.date.accessioned2016-02-28T05:52:46Zen
dc.date.available2016-02-28T05:52:46Zen
dc.date.issued2014-05en
dc.identifier.citationAgha-mohammadi A, Agarwal S, Mahadevan A, Chakravorty S, Tomkins D, et al. (2014) Robust online belief space planning in changing environments: Application to physical mobile robots. 2014 IEEE International Conference on Robotics and Automation (ICRA). Available: http://dx.doi.org/10.1109/ICRA.2014.6906602.en
dc.identifier.doi10.1109/ICRA.2014.6906602en
dc.identifier.urihttp://hdl.handle.net/10754/599525en
dc.description.abstract© 2014 IEEE. Motion planning in belief space (under motion and sensing uncertainty) is a challenging problem due to the computational intractability of its exact solution. The Feedback-based Information RoadMap (FIRM) framework made an important theoretical step toward enabling roadmap-based planning in belief space and provided a computationally tractable version of belief space planning. However, there are still challenges in applying belief space planners to physical systems, such as the discrepancy between computational models and real physical models. In this paper, we propose a dynamic replanning scheme in belief space to address such challenges. Moreover, we present techniques to cope with changes in the environment (e.g., changes in the obstacle map), as well as unforeseen large deviations in the robot's location (e.g., the kidnapped robot problem). We then utilize these techniques to implement the first online replanning scheme in belief space on a physical mobile robot that is robust to changes in the environment and large disturbances. This method demonstrates that belief space planning is a practical tool for robot motion planning.en
dc.description.sponsorshipThis research supported in part by AFOSR GrantFA9550-08-1-0038 and by NSF awards CNS-0551685, CCF-0833199,CCF-0830753, IIS-0916053, IIS-0917266, EFRI-1240483, RI-1217991, byNIH NCI R25 CA090301-11, by Chevron, IBM, Intel, Oracle/Sun and byAward KUS-C1-016-04, made by King Abdullah University of Scienceand Technology (KAUST). J. Denny supported in part by an NSF GraduateResearch Fellowship.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.titleRobust online belief space planning in changing environments: Application to physical mobile robotsen
dc.typeConference Paperen
dc.identifier.journal2014 IEEE International Conference on Robotics and Automation (ICRA)en
dc.contributor.institutionMassachusetts Institute of Technology, Cambridge, United Statesen
dc.contributor.institutionDept. of Aerospace Engineering, , United Statesen
dc.contributor.institutionTexas A and M University, College Station, United Statesen
kaust.grant.numberKUS-C1-016-04en
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