Abstract
The distance between sets is a long-standing computational geometry problem. In robotics, the distance between convex sets with Minkowski sum structure plays a fundamental role in collision detection. However, it is typically nontrivial to be computed, even if the projection onto each component set admits explicit formula. In this paper, we explore the problem of calculating the distance between convex sets arising from robotics. Upon the recent progress in convex optimization community, the proposed model can be efficiently solved by the recent hot-investigated first-order methods, e.g., alternating direction method of multipliers or primal-dual hybrid gradient method. Preliminary numerical results demonstrate that those first-order methods are fairly efficient in solving distance problems in robotics.
| Original language | English |
|---|---|
| Pages (from-to) | 465-490 |
| Number of pages | 26 |
| Journal | Computational Optimization and Applications |
| Volume | 77 |
| Issue number | 2 |
| DOIs | |
| State | Published - 1 Nov 2020 |
Keywords
- Alternating direction method of multipliers
- Collision detection
- Distance
- Minkowski sum of sets
- Primal-dual hybrid gradient method
- Projection
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