Addressing Cost-Space Chasms in Manipulation Planning

Dmitry Berenson, Thierry Simeon, and Siddhartha Srinivasa
IEEE International Conference on Robotics and Automation (ICRA '11), May, 2011.


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Abstract
Finding paths in high-dimensional spaces becomes difficult when we wish to optimize the cost of a path in addition to obeying feasibility constraints. Recently the T-RRT algorithm was presented as a method to plan in high-dimensional cost-spaces and it was shown to perform well across a variety of problems. However, since the T-RRT relies solely on sampling to explore the space, it has difficulty navigating cost-space chasms--narrow low-cost regions surrounded by increasing cost. Such chasms are particularly common in planning for manipulators because many useful cost functions induce narrow or lower-dimensional low-cost areas. This paper presents the GradienT-RRT algorithm, which combines the T-RRT with a local gradient method to bias the search toward lower-cost regions. GradienT-RRT is effective at navigating chasms because it explores low-cost regions that are too narrow to explore by sampling alone. We compare the performance of T-RRT and GradienT-RRT on planning problems involving cost functions defined in workspace, task space, and C-space. We find that GradienT-RRT outperforms T-RRT in terms of the cost of the final path while maintaining better or comparable computation time. We also find that the cost of paths generated by GradienT-RRT is far less sensitive to changes in a key parameter, making it easier to tune the algorithm. Finally, we conclude with a demonstration of GradienT-RRT on a planning-with-uncertainty task on the physical HERB robot.

Keywords
manipulation planning, planning with cost, planning with uncertainty, motion planning

Notes
Sponsor: LAAS-CNRS, NSF
Associated Center(s) / Consortia: Quality of Life Technology Center, National Robotics Engineering Center, and Center for the Foundations of Robotics
Associated Lab(s) / Group(s): Personal Robotics
Note: Differences from version published in ICRA 2011. Note: These changes have already been made to the PDF available on this site. 1. In algorithm 3, line 2: "c_j < c_i" is not the correct notation, it should be: "C(q_s) < C(q^{old}_s)" (Thanks to Konstantin Seiler for catching this one)

Text Reference
Dmitry Berenson, Thierry Simeon, and Siddhartha Srinivasa, "Addressing Cost-Space Chasms in Manipulation Planning," IEEE International Conference on Robotics and Automation (ICRA '11), May, 2011.

BibTeX Reference
@inproceedings{Berenson_2011_6798,
   author = "Dmitry Berenson and Thierry Simeon and Siddhartha Srinivasa",
   title = "Addressing Cost-Space Chasms in Manipulation Planning",
   booktitle = "IEEE International Conference on Robotics and Automation (ICRA '11)",
   month = "May",
   year = "2011",
   Notes = "Differences from version published in ICRA 2011. Note: These changes have already been made to the PDF available on this site. 1. In algorithm 3, line 2: "c_j < c_i" is not the correct notation, it should be: "C(q_s) < C(q^{old}_s)" (Thanks to Konstantin Seiler for catching this one)"
}