Title :
Sensor fusion for autonomous outdoor navigation using neural networks
Author :
Davis, Ian Lane ; Stentz, Anthony
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
For many navigation tasks, a single sensing modality is sufficiently rich to accomplish the desired motion control goals; for practical autonomous outdoor navigation, a single sensing modality is a crippling limitation on what tasks can be undertaken. Using a neural network paradigm particularly well suited to sensor fusion the authors have successfully performed simulated and real-world navigation tasks that required the use of multiple sensing modalities
Keywords :
computerised navigation; feedforward neural nets; mobile robots; motion control; multilayer perceptrons; path planning; sensor fusion; autonomous outdoor navigation; motion control goals; multiple sensing modalities; neural networks; real-world navigation tasks; sensor fusion; Charge coupled devices; Charge-coupled image sensors; Hidden Markov models; Mobile robots; Motion control; Navigation; Neural networks; Remotely operated vehicles; Roads; Sensor fusion;
Conference_Titel :
Intelligent Robots and Systems 95. 'Human Robot Interaction and Cooperative Robots', Proceedings. 1995 IEEE/RSJ International Conference on
Conference_Location :
Pittsburgh, PA
Print_ISBN :
0-8186-7108-4
DOI :
10.1109/IROS.1995.525906