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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Denny, J. Morales, M. Rodriguez, S. Amato, N.M. |
| Copyright Year | 2013 |
| Description | Author affiliation: Acad. Dept. of Digital Syst., Inst. Tecnol. Autonomo de Mexico, Progreso, Mexico (Morales, M.) || Dept. of Comput. Sci. & Eng., Texas A&M Univ., College Station, TX, USA (Denny, J.; Rodriguez, S.; Amato, N.M.) |
| Abstract | Rapidly-exploring Random Trees (RRTs) are effective for a wide range of applications ranging from kinodynamic planning to motion planning under uncertainty. However, RRTs are not as efficient when exploring heterogeneous environments and do not adapt to the space. For example, in difficult areas an expensive RRT growth method might be appropriate, while in open areas inexpensive growth methods should be chosen. In this paper, we present a novel algorithm, Adaptive RRT, that adapts RRT growth to the current exploration area using a two level growth selection mechanism. At the first level, we select groups of expansion methods according to the visibility of the node being expanded. Second, we use a cost-sensitive learning approach to select a sampler from the group of expansion methods chosen. Also, we propose a novel definition of visibility for RRT nodes which can be computed in an online manner and used by Adaptive RRT to select an appropriate expansion method. We present the algorithm and experimental analysis on a broad range of problems showing not only its adaptability, but efficiency gains achieved by adapting exploration methods appropriately. |
| Sponsorship | IEEE Ind. Electron. Soc. |
| Starting Page | 1772 |
| Ending Page | 1778 |
| File Size | 367279 |
| Page Count | 7 |
| File Format | |
| ISSN | 21530858 |
| DOI | 10.1109/IROS.2013.6696589 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-11-03 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Measurement Robots Planning Space exploration Vectors Vegetation Standards |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Systems Engineering Computer Science Applications Computer Vision and Pattern Recognition Software |
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