CS 326 A: Motion PlanningMain ApproachesDynamic Collision CheckingSlide 4Feature Tracking MethodsCombining Bounding Volume and Feature Tracking MethodsCS 326 A: Motion CS 326 A: Motion PlanningPlanningrobotics.stanford.edu/~latombe/cs326/2003/index.htmCollision DetectionCollision Detectionand Distance and Distance Computation:Computation:Feature Tracking Feature Tracking MethodsMethodsMain ApproachesMain ApproachesHierarchical bounding volume hierarchies Feature tracking (pairs of closest features)With Bounding Volume Hierarchies Dynamic Collision CheckingDynamic Collision Checking1232333With Feature Tracking: Dynamic Collision CheckingDynamic Collision CheckingParticularly useful when the motion is checked while being executed, e.g., as in haptics.Requires spatio-temporal assumption to be satisfied:Under a small relative motion of the objects, the tracked features change undergo small changesFeature Tracking Feature Tracking MethodsMethodsOnly update the tracked features at “critical events” when they may change KDS (Kinetic Data Structure methods) [Guibas]Fixed or arbitrary small discretizationThis class’s papers:Lin and Canny method V-Clip (Mirtich) Application to detecting self-collisions in humanoid robots (Kuffner et al.)Combining Bounding Combining Bounding Volume and Feature Volume and Feature Tracking MethodsTracking MethodsT.Y. Li and J.S. Chen. 1998. Incremental 3D Collision Detection with Hierar-chical Data Structures,Proc. ACM Symp. on Virtual Reality Software and Technology, p.139-144, Taipei,
View Full Document
Unlocking...