Learning metric-topological maps for indoor mobile robot navigation
Artificial Intelligence
Using Real-Time Stereo Vision for Mobile Robot Navigation
Autonomous Robots
Exploring artificial intelligence in the new millennium
Learning Occupancy Grid Maps with Forward Sensor Models
Autonomous Robots
An Occupancy Grids Building Method with Sonar Sensors Based on Improved Neural Network Model
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Effective maximum likelihood grid map withconflict evaluation filter using sonar sensors
IEEE Transactions on Robotics
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Evidence reasoning machine based on DSmT for mobile robot mapping in unknown dynamic environment
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Detecting free space and obstacles in omnidirectional images
ICIRA'11 Proceedings of the 4th international conference on Intelligent Robotics and Applications - Volume Part I
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In this paper, a modified method for occupancy grid map building by a moving mobile robot and a scanning ultrasonic range-finder is proposed. The map building process consists of two phases: (1) gleaning of information from environment, and (2) sonar data processing. For sonar data processing the proposed modified method combines: (1) statistical approach for probability sonar model building; and (2) application of fuzzy logic theory for sonar data fusion. It is experimentally shown that, in some applications, the proposed modified method has advantages over other well-known methods.