Reasoning with Uncertainty in Robotics International Workshop, RUR '95, Amsterdam, The Netherlands, December 4-6, 1995. Proceedings
This book presents the refereed proceedings of the International Workshop on Reasoning with Uncertainty in Robotics, RUR'95, held in Amsterdam, The Netherlands, in December 1995. The book contains 13 revised full papers carefully selected for presentation during the workshop together with six i...
| Other Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
1996, 1996
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| Edition: | 1st ed. 1996 |
| Series: | Lecture Notes in Artificial Intelligence
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- Mathematical foundations of navigation and perception for an autonomous mobile robot
- Reasoning with uncertainty in AI
- Robot navigation: Integrating perception, environmental constraints and task execution within a probabilistic framework
- Uncertainty reasoning in object recognition by image processing
- Partially observable markov decision processes for artificial intelligence
- An evidential approach to probabilistic map-building
- Belief formation by constructing models
- Causal relevance
- The robot control strategy in a domain with dynamical obstacles
- Reasoning about noisy sensors (and effectors) in the situation calculus
- Recursive total least squares: An alternative to using the discrete kalman filter in robot navigation
- A sensor-based motion planner for mobile robot navigation with uncertainty
- Knowledge considerations in robotics
- Neural network applications in sensor fusion for an autonomous mobile robot
- Structuring uncertain knowledge with hierarchical bayesiannetworks
- Uncertainty treatment in a surface filling mobile robot
- Probabilistic map learning: Necessity and difficulties
- Robot navigation with markov models: A framework for path planning and learning with limited computational resources
- A refined method for occupancy grid interpretation
- Sensor planning with bayesian decision theory
- Perception-based self-localization using fuzzy locations