DocumentCode :
2777305
Title :
Autonomous compliant motion: the Bayesian approach
Author :
Bruyninckx, Herman ; De Schutter, Joris ; Lefebvre, Tine
Author_Institution :
Dept. of Mech. Eng., Katholieke Univ., Leuven, Belgium
Volume :
3
fYear :
2000
fDate :
2000
Firstpage :
2310
Abstract :
This paper gives an overview of the different levels of sensor processing complexity found in force controlled tasks, and explains which techniques from Bayesian probability theory are appropriate to cope with uncertainties and missing information at each of the different levels. The paper reduces all approaches for “intelligent” compliant, motion sensor processing to a basis set of just four classes. Some of these algorithms have already been tested experimentally, while others are still beyond the current state-of-the-art. The major contribution of this paper is to bring a clear structure to the field, which should eventually result in an easier integration of different research results, and a more precise discussion about their relative merits and innovations
Keywords :
Bayes methods; compliance control; force control; intelligent control; probability; robots; Bayes method; autonomous compliant motion; compliance control; force control; intelligent control; motion control; motion sensor; probability; robotics; sensor processing; Bayesian methods; Force control; Force sensors; Mechanical engineering; Mechanical sensors; Robot control; Robot sensing systems; Robot vision systems; Service robots; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems, 2000. (IROS 2000). Proceedings. 2000 IEEE/RSJ International Conference on
Conference_Location :
Takamatsu
Print_ISBN :
0-7803-6348-5
Type :
conf
DOI :
10.1109/IROS.2000.895313
Filename :
895313
Link To Document :
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