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Benchmarking Sampling-, Search-, and Optimization-based Approaches for Time-Optimal Kinodynamic Mobile Robot Motion Planning

Authors: Wolfgang Hönig, Joaquim Ortiz-Haro, Marc Toussaint

Published: 2022 (Workshop Paper)

Source: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Summary

Benchmarks and compares sampling-, search-, and optimization-based planners for time-optimal kinodynamic mobile robot motion planning, providing an empirical evaluation of modern approaches.

Abstract

We consider time-optimal motion planning for dynamical systems that are translation-invariant, a property that holds for many mobile robots, such as differential-drives, cars, airplanes, and multirotors. Previous benchmarks have typically focused on comparing approaches within the same algorithmic class, e.g., sampling-based approaches may be benchmarked using the open motion planning library (OMPL). We provide the first benchmark that compares search-, sampling-, and optimization-based time-optimal motion planning on multiple dynamical systems in different settings.

Primary

Paper motion-planning-workshop.kavrakilab.org

Alternate

motion-planning-workshop.kavrakilab.org motion-planning-workshop.kavrakilab.org

Tags

  • Benchmarking

  • Kinodynamic planning

  • Mobile robots

  • Sampling-based planning

  • Search-based planning

  • Trajectory optimization

  • Time-optimal planning