Distributed Manipulation
By: edited by Karl F. Böhringer, Howie Choset
Contributors: Choset, Howie
Publisher: Springer US
Published: 2000
Place of publication: Boston, MA
Language: eng
Format: [electronic resource] /
Number of pages: 272
ISBN-13: 9781461370512; 9781461545453
Subjects: Artificial intelligence; Computer engineering; Engineering; Mechanical engineering
Description: Distributed manipulation effects motion on objects through a large number of points of contact. The primary benefit of distributed manipulators is that many small inexpensive mechanisms can move and transport large heavy objects. In fact, each individual component is simple, but their combined effect is quite powerful. Furthermore, distributed manipulators are fault-tolerant because if one component breaks, the other components can compensate for the failure and the whole system can still perform its task. Finally, distributed manipulators can perform a variety of tasks in parallel. Distributed manipulation can be performed by many types of mechanisms at different scales. Due to the recent advances of MEMS (micro-electro-mechanical system) technology, it has become feasible to quickly manufacture distributed micro-manipulators at low cost. One such system is an actuator array where hundreds of micro-scaled actuators transport and manipulate small objects that rest on them. Macroscopic versions of the actuator array have also been developed and analyzed. Another form of distributed manipulation is derived from a vibrating plate, and teams of mobile robots have been used to herd large objects into desired locations. There are many fundamental issues involved in distributed manipulation. Since a distributed manipulator has many actuators, distributed control strategies must be considered to effectively manipulate objects. A basic understanding of contact analysis between the actuators and object must also be considered. When each actuator in the array has a sensor, distributed sensing presents some basic research challenges. Distributed computation and communication are key issues to enable the successful deployment of distributed manipulators into use. Finally, the trade-off in centralized and de-centralized approaches in all of these algorithms must be investigated.
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