Please use this identifier to cite or link to this item:
https://doi.org/10.1007/978-3-642-14743-2_23
DC Field | Value | |
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dc.title | Motion planning for 3-D target tracking among obstacles | |
dc.contributor.author | Bandyopadhyay, T. | |
dc.contributor.author | Ang Jr., M.H. | |
dc.contributor.author | Hsu, D. | |
dc.date.accessioned | 2013-07-23T09:29:38Z | |
dc.date.available | 2013-07-23T09:29:38Z | |
dc.date.issued | 2010 | |
dc.identifier.citation | Bandyopadhyay, T.,Ang Jr., M.H.,Hsu, D. (2010). Motion planning for 3-D target tracking among obstacles. Springer Tracts in Advanced Robotics 66 (STAR) : 267-279. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-14743-2_23" target="_blank">https://doi.org/10.1007/978-3-642-14743-2_23</a> | |
dc.identifier.isbn | 9783642147425 | |
dc.identifier.issn | 16107438 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/43272 | |
dc.description.abstract | The goal of target tracking is to compute motion strategies for a robot equipped with visual sensors, so that it can effectively track a moving target despite obstruction by obstacles. It is an important problem with many applications in robotics. Existing work focuses mostly on the 2-D version of the problem, partly due to the complexity of dealing with 3-D visibility relationships. This paper proposes an online algorithm for 3-D target tracking among obstacles, using only local geometric information available to a robot's visual sensors. Key to this new algorithm is the definition and efficient computation of a risk function, which tries to capture a target's ability in escaping from the robot sensors' visibility region in both short and long terms. The robot then moves to minimize this risk function locally in a greedy fashion. In the absence of occlusion by obstacles, the standard tracking algorithm based on visual servo control can be considered a special case of our algorithm. Experiments show that the new algorithm generated interesting tracking behaviors in three dimensions and performed substantially better than visual servo control in simulation. © 2010 Springer-Verlag Berlin Heidelberg. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-14743-2_23 | |
dc.source | Scopus | |
dc.type | Conference Paper | |
dc.contributor.department | COMPUTER SCIENCE | |
dc.contributor.department | MECHANICAL ENGINEERING | |
dc.description.doi | 10.1007/978-3-642-14743-2_23 | |
dc.description.sourcetitle | Springer Tracts in Advanced Robotics | |
dc.description.volume | 66 | |
dc.description.issue | STAR | |
dc.description.page | 267-279 | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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