Abstract:
We propose a novel method adaptive subdivision (AS) to evaluate the distance function for moving general polygonal models. The distance function can have a positive and a...Show MoreNotes: This article was mistakenly omitted from the original submission to IEEE Xplore. It is now included as part of the conference record.
Metadata
Abstract:
We propose a novel method adaptive subdivision (AS) to evaluate the distance function for moving general polygonal models. The distance function can have a positive and a negative value, each of which corresponds to the Euclidean distance and penetration depth, respectively. In our approach, the distance between a pair of objects can be evaluated along any time interval of the object’s trajectory; therefore it is called “continuous”, and a minimum of the continuous distance (MCD) is determined for collision avoidance. In order to compute a MCD for general polygonal models, we calculate the upper and lower bounds of the distance in the time interval and abandons the time intervals that cannot realize the MCD. We have implemented our distance evaluation method, and have experimentally validated the proposed methods to effectively and accurately find the MCDs to generate a collision-free motion for the HRP-2 humanoid robot.
Notes: This article was mistakenly omitted from the original submission to IEEE Xplore. It is now included as part of the conference record.
Date of Conference: 20-24 May 2019
Date Added to IEEE Xplore: 30 January 2020
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