Modeling a dynamic environment using a Bayesian multiple hypothesis approach
Artificial Intelligence
Directed Sonar Sensing for Mobile Robot Navigation
Directed Sonar Sensing for Mobile Robot Navigation
Using Real-Time Stereo Vision for Mobile Robot Navigation
Autonomous Robots
Enhancement of Probabilistic Grid-based Map for Mobile Robot Applications
Journal of Intelligent and Robotic Systems
A Navigation System for Assistant Robots Using Visually Augmented POMDPs
Autonomous Robots
International Journal of Robotics Research
Robot path planning using SIFT and sonar sensor fusion
ROCOM'07 Proceedings of the 7th WSEAS International Conference on Robotics, Control & Manufacturing Technology
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
Robotic Mapping Using Measurement Likelihood Filtering
International Journal of Robotics Research
Online world modeling and path planning for an unmanned helicopter
Autonomous Robots
Contextual occupancy maps using Gaussian processes
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Survey of Motion Planning Literature in the Presence of Uncertainty: Considerations for UAV Guidance
Journal of Intelligent and Robotic Systems
Evaluating techniques for resolving redundant information and specularity in occupancy grids
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Gaussian process occupancy maps*
International Journal of Robotics Research
An Approach for 2D Visual Occupancy Grid Map Using Monocular Vision
Electronic Notes in Theoretical Computer Science (ENTCS)
Laser and Radar Based Robotic Perception
Foundations and Trends in Robotics
Robotics and Autonomous Systems
Improved occupancy grid mapping in specular environment
Robotics and Autonomous Systems
A generative model for online depth fusion
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
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Occupancy grids are a probabilistic method for fusing multiplesensor readings into surface maps of the environment. Although theunderlying theory has been understood for many years, the intricacies ofapplying it to realtime sensor interpretation have been neglected. Thispaper analyzes how refined sensor models (including specularity models) andassumptions about independence are crucial issues for occupancy gridinterpretation. Using this analysis, the MURIEL method for occupancy gridupdate is developed. Experiments show how it can dramatically improve thefidelity of occupancy grid map-making in specular and realtimeenvironments.