Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Navigation guided by artificial force fields
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Introduction to AI Robotics
Robot Motion Planning
CubicalPath - Dynamic Potential Fields for Guided Exploration in Virtual Environments
PG '00 Proceedings of the 8th Pacific Conference on Computer Graphics and Applications
An intelligent 3D user interface adapting to user control behaviors
Proceedings of the 9th international conference on Intelligent user interfaces
Potential field based camera collisions detection in a static 3D environment
Machine Graphics & Vision International Journal
Potential Field Based Camera Collisions Detection within Translating 3D Objects
ICCVG 2008 Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers
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Existing collision detection methods usually need long precalculation stage or difficult, time-consuming real-time computation. Moreover, their effectiveness considerably decreases with the growth of the complexity of the scene. Especially dynamic scenes with moving objects require the necessity of each frame collisions recalculation due to changeable objects' position and orientation. So far seemingly promising solutions supported by potential fields do not introduce satisfactory functionality as they are mainly devoted to static scenes with one predefined goal. This paper introduces a method which offers a new dynamic GPU supported potential field construction which lets the camera collide with both dynamic and static objects. Additionally, the proposed method does not need pre-calculation stage and provides an almost scenecomplexity independent solution. The presented method is based on an arbfp1 shader solution1, which means that most contemporary graphics cards can operate it without constraints