Real-Time Optimization-Based Planning in Dynamic Environments Using GPUs

Authors

  • Chonhyon Park University of North Carolina at Chapel Hill
  • Jia Pan University of North Carolina at Chapel Hill
  • Dinesh Manocha University of North Carolina at Chapel Hill

DOI:

https://doi.org/10.1609/socs.v3i1.18263

Keywords:

Robot Motion Planning, Dynamic Environment, Real-time Planning

Abstract

We present a novel algorithm to compute collision-free trajectories in dynamic environments. Our approach is general and makes no assumption about the obstacles or their motion. We use a replanning framework that interleaves optimization-based planning with execution. Furthermore, we describe a parallel formulation that exploits high number of cores on commodity graphics processors (GPUs) to compute a high-quality path in a given time interval. Overall, we show that search in configuration spaces can be significantly accelerated by using GPU parallelism.

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Published

2021-08-20