In this work, we present our view of an intelligent robotic manipulator that can work autonomously in a dynamically changing environment. The increased intelligence is needed to enable the manipulator to react to changing environments without contacting a supervising coordinator. This approach requires increased computational capabilities on the part of the manipulator. We show how the computational requirements of such an autonomous manipulator can be satisfied by a combination of neural network-based processing modules. We use symbolic computation methods to construct these neural networks (thereby eliminating training times), and sensors to provide the signals to recognize changes in the environment.
|Number of pages||6|
|Journal||Proceedings of the IEEE International Conference on Systems, Man and Cybernetics|
|Publication status||Published - 1995|
|Event||Proceedings of the 1995 IEEE International Conference on Systems, Man and Cybernetics. Part 2 (of 5) - Vancouver, BC, Can|
Duration: 22 Oct 1995 → 25 Oct 1995