Title :
Neural computation for planning AND/OR precedence-constraint robot assembly sequences
Author :
Chen, C. L Philip
Abstract :
The problem of finding AND/OR precedence-constraint assembly sequences for a set of n parts that construct a mechanical object using neural computation is discussed. The geometric constraints of the assembled object are transformed into the elements of the connection matrix which specifies the connection strength among neurons. A modified Hopfield network is used to tackle the AND/OR precedence-constraint assembly-sequence problem. The designed algorithm can accommodate various constraints and applications. Detailed algorithms and analysis, and examples and experiments are presented
Keywords :
assembling; neural nets; operations research; robots; AND/OR precedence-constraint; connection matrix; geometric constraints; modified Hopfield network; neural computation; planning; precedence-constraint assembly sequences; robot assembly sequences;
Conference_Titel :
Neural Networks, 1990., 1990 IJCNN International Joint Conference on
Conference_Location :
San Diego, CA, USA
DOI :
10.1109/IJCNN.1990.137557