Referenced Items are not available for this document.
Robotics has provided the motivation and inspiration for many innovations in planning and control. From nonholonomic motion planning [1] to probabilistic road maps [2], from capture basins [3] to preimages [4] of obstacles to avoid, and from geometric nonlinear control [5], [6] to machine-learning methods in robotic control [7], there is a wide range of planning and control algorithms and methodologies that can be traced back to a perceived need or anticipated benefit in autonomous or semiautonomous systems.
Published in:
Robotics & Automation Magazine, IEEE
(Volume:18
,
Issue:
3
)
Date of Publication: Sept. 2011
- Page(s):
- 33 - 43
- ISSN :
- 1070-9932
- INSPEC Accession Number:
- 12219006
- Digital Object Identifier :
- 10.1109/MRA.2011.942113
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 12 September 2011
- Issue Date :
- Sept. 2011
- Sponsored by :
- IEEE Robotics and Automation Society
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