Case-based reasoning
Learning metric-topological maps for indoor mobile robot navigation
Artificial Intelligence
Probabilistic robot navigation in partially observable environments
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
A multi-agent architecture with cooperative fuzzy control for a mobile robot
Robotics and Autonomous Systems
Temporal-Bounded CBR for the Management of Commitments in RT-Agents
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
Incorporating temporal-bounded CBR techniques in real-time agents
Expert Systems with Applications: An International Journal
Genetic algorithm based solution to dead-end problems in robot navigation
International Journal of Computer Applications in Technology
Retrieving and reusing game plays for robot soccer
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
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In this paper we propose the use of case-based reasoning techniques to improve the navigation of an autonomous robot in unknown semistructured environments. At the moment the current goal is to identify problematic situations (such as dead ends or obstacle layouts that the robot is not able to avoid) and take the proper actions in order to avoid them. As the first steps we propose a similarity function to retrieve similar past cases. We integrate a CBR agent into an existing multiagent navigation system in order to evaluate the performance of the CBR system. The results obtained through simulation show that the new system not only prevents the robot from getting blocked in certain situations, but also improves the performance in terms of time and distance of the path taken to reach the target.