Computational principles of mobile robotics
Computational principles of mobile robotics
An Behavior-based Robotics
Fuzzy Motion Planning of Mobile Robots in Unknown Environments
Journal of Intelligent and Robotic Systems
Learning Occupancy Grid Maps with Forward Sensor Models
Autonomous Robots
Sensor-based fuzzy reactive navigation of a mobile robot throughlocal target switching
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Real-time map building and navigation for autonomous robots inunknown environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Learning sensor-based navigation of a real mobile robot in unknownworlds
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Integration of reactive behaviors and enhanced topological map for robust mobile robot navigation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Map-based navigation in mobile robots
Cognitive Systems Research
Map-based navigation in mobile robots
Cognitive Systems Research
Development of a new minimum avoidance system for a behavior-based mobile robot
Fuzzy Sets and Systems
Expert Systems with Applications: An International Journal
Formation and obstacle-avoidance control for mobile swarm robots based on artificial potential field
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
A fuzzy logic based multi-agents controller
Expert Systems with Applications: An International Journal
Development of the binocular-vision-enhanced mobile robot navigation
International Journal of Intelligent Systems Technologies and Applications
Fuzzy embedded mobile robot systems design through the evolutionary PSO learning algorithm
WSEAS TRANSACTIONS on SYSTEMS
An expert fuzzy cognitive map for reactive navigation of mobile robots
Fuzzy Sets and Systems
Robust Reactive Mobile Robot Navigation with Modified DWA+CG
Proceedings of Conference on Advances In Robotics
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
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The proposed approach in this paper involves a new grid-based map model called ''memory grid'' and a new behavior-based navigation method called ''minimum risk method''. The memory grid map records not only the environmental information, but also the robot experience. The minimum risk method is just one of the applications of the memory grid technique, which addresses the local minimum problem faced by a goal-oriented robot navigating in unknown indoor environments. The Minimum Risk implies that the robot is able to choose the safest region that can avoid colliding with obstacles and prevent the robot from iterating previous trajectory. This method is demonstrated to work in long wall, large concave, recursive U-shaped, unstructured, cluttered, maze-like, and dynamic indoor environments. It adopts a strategy of multi-behavior coordination in which a novel path-searching behavior is developed to recommend the region offering the minimum risk. Fuzzy logic is used to implement the behavior design and coordination. The proposed approach is verified with simulation and real-world tests.