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Content Provider | IEEE Xplore Digital Library |
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Author | Lobaton, E. Jinghe Zhang Patil, S. Alterovitz, R. |
Copyright Year | 2011 |
Description | Author affiliation: Department of Computer Science, University of North Carolina at Chapel Hill, 27599, USA (Lobaton, E.; Jinghe Zhang; Patil, S.; Alterovitz, R.) |
Abstract | We present a new sampling-based method for planning optimal, collision-free, curvature-constrained paths for nonholonomic robots to visit multiple goals in any order. Rather than sampling configurations as in standard sampling-based planners, we construct a roadmap by sampling circles of constant curvature and then generating feasible transitions between the sampled circles. We provide a closed-form formula for connecting the sampled circles in 2D and generalize the approach to 3D workspaces. We then formulate the multigoal planning problem as finding a minimum directed Steiner tree over the roadmap. Since optimally solving the multi-goal planning problem requires exponential time, we propose greedy heuristics to efficiently compute a path that visits multiple goals. We apply the planner in the context of medical needle steering where the needle tip must reach multiple goals in soft tissue, a common requirement for clinical procedures such as biopsies, drug delivery, and brachytherapy cancer treatment. We demonstrate that our multi-goal planner significantly decreases tissue that must be cut when compared to sequential execution of single-goal plans. |
Starting Page | 1463 |
Ending Page | 1469 |
File Size | 369078 |
Page Count | 7 |
File Format | |
ISBN | 9781612843865 |
ISSN | 10504729 |
e-ISBN | 9781612843858 |
DOI | 10.1109/ICRA.2011.5980446 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2011-05-09 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Needles Planning Bridges Joining processes Robot kinematics Approximation algorithms |
Content Type | Text |
Resource Type | Article |
Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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