Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Searching for a mobile intruder in a polygonal region
SIAM Journal on Computing
Sequential Operations in Digital Picture Processing
Journal of the ACM (JACM)
A team of robotic agents for surveillance
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Evolving robot behavior to play hide and seek
Journal of Computing Sciences in Colleges
The focussed D* algorithm for real-time replanning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
On reduced time fault tolerant paths for multiple UAVs covering a hostile terrain
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Optimal Global Path Planning in Time Varying Environments Based on a Cost Evaluation Function
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Roadmap-based stealth navigation for intercepting an invader
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Computing highly occluded paths on a terrain
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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A new promising approach for visibility-sensitive path-planning problems is presented. The paper focuses on covert navigation where a mobile robot needs to plan a stealthy path to approach a designated destination in a cluttered environment. The aim is to minimize the robot's exposure to hostile sentries within the same environment. The approach can be adapted to work with different levels of initial knowledge the robot may have about both the environment map and the sentries' locations. The approach depends on estimating a cost value at each free-space location that presents the risk of being seen by any sentry. Based on the distance transform algorithm methodology, the minimum visibility–distance cost to a goal is calculated at each cell in the grid-based environment map. Moving along the steepest descent trajectory from any starting point generates an optimal covert path to a goal. The approach has been evaluated with both simulated and physical experiments. A number of test cases are presented. In each case, a path with considerable covertness, compared to a short path to the same destination, is generated. In addition to covert navigation, the approach is introduced briefly as a potential solution for other visibility-based path-planning problems.