Efficient maintenance and self-collision testing for Kinematic Chains

The kinematic chain is a ubiquitous and extensively studied representation in robotics as well as a useful model for studying the motion of biological macro-molecules. Both fields stand to benefit from algorithms for efficient maintenance and collision detection in such chains. This paper introduces a novel hierarchical representation of a kinematic chain allowing for efficient incremental updates and relative position calculation. A hierarchy of oriented bounding boxes is superimposed on this representation, enabling high performance collision detection, self-collision testing, and distance computation. This representation has immediate applications in the field of molecular biology, for speeding up molecular simulations and studies of folding paths of proteins. It could be instrumental in path planning applications for robots with many degrees of freedom, also known as hyper-redundant robots. A comparison of the performance of the algorithm with the current state of the art in collision detection is presented for a number of benchmarks.

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