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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yanyan Lu Zhonghua Xi Jyh-Ming Lien |
| Copyright Year | 2014 |
| Description | Author affiliation: Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA (Yanyan Lu; Zhonghua Xi; Jyh-Ming Lien) |
| Abstract | Collision prediction is a fundamental operation for planning motion in dynamic environment. Existing methods usually exploit complex behavior models or use dynamic constraints in collision prediction. However, these methods all assume simple geometries, such as disc, which significantly limit their applicability. This paper proposes a new approach that advances collision prediction beyond disc robots and handles arbitrary polygons. Our new tool predicts collision by assuming that obstacles are adversarial. Comparing to an online motion planner that replans periodically at fixed time interval and planner that approximates obstacle with discs, our experimental results provide strong evidences that the new method significantly reduces the number of replans while maintaining higher success rate of finding a valid path. Our geometric-based collision prediction method provides a tool to handle highly complex shapes and provides a complimentary approach to those methods that consider behavior and dynamic constraints of objects with simple shapes. |
| Starting Page | 4148 |
| Ending Page | 4153 |
| File Size | 477193 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781479969340 |
| DOI | 10.1109/IROS.2014.6943147 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-09-14 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Collision avoidance Planning Dynamics Shape Robot sensing systems Trajectory |
| Content Type | Text |
| Resource Type | Article |
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