Vision for Mobile Robot Navigation: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Behavior-based Robotics
Explanation-Driven Case-Based Reasoning
EWCBR '93 Selected papers from the First European Workshop on Topics in Case-Based Reasoning
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
High-Level Behavior Programming
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Stratified case-based reasoning: reusing hierarchical problem solving episodes
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Pure reactive behavior learning using Case Based Reasoning for a vision based 4-legged robot
Robotics and Autonomous Systems
Case-based reasoning emulation of persons for wheelchair navigation
Artificial Intelligence in Medicine
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This paper presents a new approach to building low level navigation behaviors for 4-legged robots through vision based demonstration learning. The main novelty of the approach is that rather than observing other entities and adapting their kinematics to the robot constraints, a supervisor controls the robot to achieve the desired behavior through a proper interface. The guided actions and the relevant input parameters are related via Case Base Reasoning, so that the robot can retrieve them later to work in an unsupervised way. This intuitive acquisition of reactive behaviors allows bottom-up construction of more complex emergent behaviors and avoids low level kinematics analysis and possible associated errors. The system has been successfully tested using a Sony Aibo robot. Experiments have proven that the robot is capable of adopting a variety of reliable behaviors depending on its relative position in relation to a ball through different trainings. Also, being reactive, the system is resistant against punctual errors and occlusions.