Title :
Self-organizing sensors by deterministic annealing
Author :
Hackwood, Susan ; Beni, Gerardo
Author_Institution :
Coll. of Eng., California Univ., Riverside, CA, USA
Abstract :
Proposes a new method of robot self-organization for a class of robotic tasks which cannot be carried out by a single robot but must be carried out by a group of robots. The authors make use of a deterministic `reverse´ annealing clustering method based on a maximum-minimum entropy solution. They show that this reverse annealing method, which results in a better way of escaping local minima than other fuzzy clustering methods, is well suited to applications in distributed robotics since it provides a natural way of following the self-organizing evolution of a system of robots. In particular, two opposite classes of self-organizing behavior are studied: the self-organization `from few groups to many units´ and the self-organization `from many units to a few groups´
Keywords :
entropy; robots; self-adjusting systems; simulated annealing; deterministic annealing; distributed robotics; maximum-minimum entropy; reverse annealing; robot; self adjusting systems; self-organization; Acoustic sensors; Annealing; Cameras; Chemical sensors; Clustering methods; Intelligent robots; Magnetic sensors; Robot sensing systems; Robot vision systems; Thermal sensors;
Conference_Titel :
Intelligent Robots and Systems '91. 'Intelligence for Mechanical Systems, Proceedings IROS '91. IEEE/RSJ International Workshop on
Conference_Location :
Osaka
Print_ISBN :
0-7803-0067-X
DOI :
10.1109/IROS.1991.174658