DocumentCode :
2804360
Title :
Assembly planning operation strategies based on the degree of constraint
Author :
Yoshikawa, Tsuneo ; Yokokohji, Yasuyoshi ; Yu, Yong
Author_Institution :
Fac. of Eng., Kyoto Univ., Japan
fYear :
1991
fDate :
3-5 Nov 1991
Firstpage :
682
Abstract :
For autonomous assembly operations by a robot, it is required to build a planning function that can generate a series of operations to reach a goal state. This paper describes an automatic planning algorithm that synthesizes the assembly operation strategies. By minimizing a criterion function based on the difficulty of state transitions the method can find an optimal path in a contact state network. The degree of constraint is proposed by regarding the assembly task as a process of changing the constraint state of the object. State transition difficulty is discussed by considering the variation of the degree of constraint and the shape information from the geometric models of objects. Then, a criterion function for state transitions is defined based on the state transition difficulty. Lastly, an algorithm which plans an optimal state transition path from an initial state to a goal state is proposed. Some examples are given to show the validity of this algorithm
Keywords :
assembling; industrial robots; planning (artificial intelligence); assembly planning operation strategies; automatic planning algorithm; autonomous assembly; constraint degree; contact state network; criteria function minimization; optimal path; optimal state transition path; robot; state transition difficulty; Error correction; Network synthesis; Position control; Process planning; Robotic assembly; Shape; Solid modeling; Strategic planning; Uncertainty;
fLanguage :
English
Publisher :
ieee
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
Type :
conf
DOI :
10.1109/IROS.1991.174557
Filename :
174557
Link To Document :
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