Planning and acting in partially observable stochastic domains
Artificial Intelligence
Robust Monte Carlo localization for mobile robots
Artificial Intelligence
Mechanics of robotic manipulation
Mechanics of robotic manipulation
FastSLAM: a factored solution to the simultaneous localization and mapping problem
Eighteenth national conference on Artificial intelligence
Visibility-based pursuit-evasion with limited field of view
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Simple Robots with Minimal Sensing: From Local Visibility to Global Geometry
International Journal of Robotics Research
Simple Robots in Polygonal Environments: A Hierarchy
Algorithmic Aspects of Wireless Sensor Networks
Simple robots with minimal sensing: from local visibility to global geometry
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Exploring Polygonal Environments by Simple Robots with Faulty Combinatorial Vision
SSS '09 Proceedings of the 11th International Symposium on Stabilization, Safety, and Security of Distributed Systems
Counting targets with mobile sensors in an unknown environment
ALGOSENSORS'07 Proceedings of the 3rd international conference on Algorithmic aspects of wireless sensor networks
Reconstructing visibility graphs with simple robots
SIROCCO'09 Proceedings of the 16th international conference on Structural Information and Communication Complexity
How simple robots benefit from looking back
CIAC'10 Proceedings of the 7th international conference on Algorithms and Complexity
Reconstructing visibility graphs with simple robots
Theoretical Computer Science
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Sensing uncertainty is a central issue in robotics. Sensor limitations often prevent accurate state estimation, and robots find themselves confronted with a complicated infonnation (belief) space. In this paper we define and characterize the information spaces of very simple robots, called Bitbots, which have severe sensor limitations. While complete estimation of the robot's state is impossible, careful consideration and management of the uncertainty is presented as a search in the information space. We show that these simple robots can solve several challenging online problems, even though they can neither obtain a complete map of their environment nor exactly localize themselves. However, when placed in an unknown environment, Bitbots can build a topological representation of it and then perform pursuit-evasion (i.e., locate all moving targets inside this environment). This paper introduces Bitbots, and provides both theoretical analysis of their information spaces and simulation results.