Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Harmonic functions and collision probabilities
International Journal of Robotics Research
Learning metric-topological maps for indoor mobile robot navigation
Artificial Intelligence
Artificial intelligence: a new synthesis
Artificial intelligence: a new synthesis
Robot Motion Planning
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Learning to Predict by the Methods of Temporal Differences
Machine Learning
A frontier-based approach for autonomous exploration
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Exploratory Navigation Based on Dynamical Boundary Value Problems
Journal of Intelligent and Robotic Systems
Exploration of a cluttered environment using Voronoi Transform and Fast Marching
Robotics and Autonomous Systems
Exploration of 2D and 3D Environments using Voronoi Transform and Fast Marching Method
Journal of Intelligent and Robotic Systems
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Sculpting potential fields in the BVP path planner
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
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Here we propose an architecture for an autonomous mobile agent that explores while mapping a two-dimensional environment. The map is a discretized model for the localization of obstacles, on top of which a harmonic potential field is computed. The potential field serves as a fundamental link between the modeled (discrete) space and the real (continuous) space where the agent operates. It indicates safe paths towards non-explored regions. Harmonic functions were originally used as global path planners in mobile robotics. In this paper, we extend its functionality to environment exploration. We demonstrate our idea through experimental results obtained using a Nomad 200 robot platform.