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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chen, P.C. |
| Copyright Year | 1994 |
| Description | Author affiliation: Sandia Nat. Labs., Albuquerque, NM, USA (Chen, P.C.) |
| Abstract | Path planning needs to be fast to facilitate real-time robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To overcome this difficulty, the author presents an adaptive algorithm that uses past experience to speed up future performance. It is a learning algorithm suitable for automating flexible manufacturing in incrementally-changing environments. The algorithm allows the robot to adapt to its environment by having two manipulation schemes. For minor environmental change, the author uses an object-attached experience abstraction scheme to increase the flexibility of the learned experience; for major environmental change, the author uses an on-demand experience repair scheme to retain those experiences that remain valid and useful. Using this algorithm, one can effectively reduce the overall robot planning time by re-using the computation result for one task to plan a path for another.< |
| Starting Page | 17 |
| Ending Page | 23 |
| File Size | 674337 |
| Page Count | 7 |
| File Format | |
| ISBN | 0818665106 |
| DOI | 10.1109/CIMAT.1994.389099 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1994-10-10 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Path planning Flexible manufacturing systems Robot programming Laboratories Adaptive algorithm Manufacturing automation Robotics and automation Technology planning Computer aided manufacturing Mobile robots |
| Content Type | Text |
| Resource Type | Article |
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