Passive map learning and visual place recognition
Passive map learning and visual place recognition
Artificial intelligence and mobile robots: case studies of successful robot systems
Artificial intelligence and mobile robots: case studies of successful robot systems
The interactive museum tour-guide robot
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots
Machine Learning - Special issue on learning in autonomous robots
Navigating Mobile Robots: Systems and Techniques
Navigating Mobile Robots: Systems and Techniques
Globally Consistent Range Scan Alignment for Environment Mapping
Autonomous Robots
Probabilistic robot navigation in partially observable environments
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Estimating the absolute position of a mobile robot using position probability grids
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Classifying and recovering from sensing failures in autonomous mobile robots
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
The interactive museum tour-guide robot
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Monte Carlo localization: efficient position estimation for mobile robots
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Experiences from the use of a robotic avatar in a museum setting
Proceedings of the 2001 conference on Virtual reality, archeology, and cultural heritage
A Probabilistic Approach to Collaborative Multi-Robot Localization
Autonomous Robots
The DD&P Robot Control Architecture (A Preliminary Report)
Revised Papers from the International Seminar on Advances in Plan-Based Control of Robotic Agents,
MINERVA: A Tour-Guide Robot that Learns
KI '99 Proceedings of the 23rd Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
Extracting Situation Facts from Activation Value Histories in Behavior-Based Robots
KI '01 Proceedings of the Joint German/Austrian Conference on AI: Advances in Artificial Intelligence
Global localization and topological map-learning for robot navigation
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
Active Appearance-Based Robot Localization Using Stereo Vision
Autonomous Robots
Object following control for wheeled mobile robots
ICAI'08 Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information
Aspects regarding the object following control procedure for wheeled mobile robots
WSEAS Transactions on Systems and Control
Memory Efficient Vision Based Line Feature Extraction for Tiny Mobile Robots
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
A novel approach to the mobile robot localization problem using tracking methods
RA '07 Proceedings of the 13th IASTED International Conference on Robotics and Applications
Combining kalman filtering and Markov localization in network-like environments
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
Sensor Fusion for SLAM Based on Information Theory
Journal of Intelligent and Robotic Systems
Improving position estimation accuracy of mobile robot by using UHF passive RFID tags
ICHIT'11 Proceedings of the 5th international conference on Convergence and hybrid information technology
Map-based navigation in mobile robots
Cognitive Systems Research
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For mobile robots to be successful, they have to navigate safely in populated and dynamic environments. While recent research has led to a variety of localization methods that can track robots well in static environments, we still lack methods that can robustly localize mobile robots in dynamic environments, in which people block the robot's sensors for extensive periods of time or the position of furniture may change. This paper proposes extensions to Markov localization algorithms enabling them to localize mobile robots even in densely populated environments. Two different filters for determining the "believability" of sensor readings are employed. These filters are designed to detect sensor readings that are corrupted by humans or unexpected changes in the environment. The technique was recently implemented and applied as part of an installation, in which a mobile robot gave interactive tours to visitors of the "Deutsches Museum Bonn." Extensive empirical tests involving datasets recorded during peak traffic hours in the museum demonstrate that this approach is able to accurately estimate the robot's position in more than 98% of the cases even in such highly dynamic environments.