Haptic Collision Detection on Disjoint Objects with Overlapping and Inclusive Bounding Volumes

Area of Science:

• Computer Science
• Robotics
• Human-Computer Interaction

Background:

• Haptic collision detection performance degrades with overlapping bounding volumes.
• Narrow phase collision detection becomes overloaded with numerous objects.

Purpose of the Study:

• To develop a method for alleviating performance degradation in haptic collision detection.
• To ensure stable performance by optimizing bounding volume management.

Main Methods:

• A hybrid approach combining bounding volume and space partitioning.
• An algorithm to generate mutually exclusive bounding volumes during pre-processing.
• Broad phase culling of irrelevant objects to reduce narrow phase load.

Main Results:

• The proposed method successfully generates tighter, exclusive bounding volumes.
• Experiments show stable haptic collision detection performance in challenging situations.
• Comparison with existing algorithms demonstrates superior performance.

Conclusions:

• The developed method effectively enhances haptic collision detection efficiency.
• Optimized bounding volume management is crucial for complex interactive systems.
• This approach maintains performance integrity under demanding conditions.