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논문검색

Terrain Mapping and Classification in Outdoor Environments Using Neural Networks

초록

영어

This paper describes a three-dimensional terrain mapping and classification technique to allow the operation of mobile robots in outdoor environments using laser range finders. We propose the use of a multi-layer perceptron neural network to classify the terrain into navigable, partially navigable, and non-navigable. The maps generated by our approach can be used for path planning, navigation, and local obstacle avoidance. Experimental tests using an outdoor robot and a laser sensor demonstrate the accuracy of the presented methods.

목차

Abstract
 1. Introduction
  1.1 Related Works
 2. Mapping
  2.1 Terrain Mapping
 3. Artificial Neural Networks
  3.1 Map Classification
 4. Results
 5. Conclusion
 References

저자정보

  • Alberto Yukinobu Hata Moblie Robotics Laboratory, University of São Paulo
  • Denis Fernando Wolf Moblie Robotics Laboratory, University of São Paulo
  • Gustavo Pessin Moblie Robotics Laboratory, University of São Paulo
  • Fernando Osório Moblie Robotics Laboratory, University of São Paulo

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