DocumentCode
1318462
Title
Hybrid Systems in Robotics
Author
Ding, Jerry ; Gillula, Jeremy H. ; Huang, Haomiao ; Vitus, Michael P. ; Zhang, Wei ; Tomlin, Claire J.
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Univ. of California, Berkeley, CA, USA
Volume
18
Issue
3
fYear
2011
Firstpage
33
Lastpage
43
Abstract
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.
Keywords
collision avoidance; mobile robots; capture basins; geometric nonlinear control; hybrid systems; machine-learning methods; nonholonomic motion planning; obstacle avoidance; probabilistic road maps; robotic control; semiautonomous systems; Hybrid intelligent systems; Machine learning; Motion planning; Robot control;
fLanguage
English
Journal_Title
Robotics & Automation Magazine, IEEE
Publisher
ieee
ISSN
1070-9932
Type
jour
DOI
10.1109/MRA.2011.942113
Filename
6016585
Link To Document