Finding critical changes in dynamic configuration spaces
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Finding Critical Changes in Dynamic Configuration Spaces. Yanyan Lu and Jyh-Ming Lien George Mason University. Problem Statement. Plan motion in dynamic workspace Dynamic obstacle moves along some known trajectory with bounded velocities.

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Finding Critical Changes in Dynamic Configuration Spaces

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Finding critical changes in dynamic configuration spaces

Finding Critical Changes in Dynamic Configuration Spaces

Yanyan Lu and Jyh-Ming Lien

George Mason University


Problem statement

Problem Statement

Plan motion in dynamic workspace

Dynamic obstacle

moves along some known trajectory

with bounded velocities

Image from “Constraint-Based Motion Planning using Voronoi Diagrams” Garber and Lin, WAFR02


Existing problems

Existing Problems

  • No reusability in

    • Traditional methods using Configuration-Time space decomposition

    • Direct application of Probabilistic Roadmap Methods (PRM) or Rapidly-Exploring Random Tree (RRT)


Existing problems1

Image from “An incremental learning approach to motion planning with roadmap management”, T-Y Li and Y-C Shie, ICRA ‘02

Existing Problems

  • More recent methods only repair the invalid portion but at fixed time interval

    • Fine time resolution results in low efficiency

    • Low time resolution results in low completeness


Our work detect topological changes of free c space

Our Work: Detect Topological Changes of Free C-Space

time of contact

time of separation

time of contact

time of contact


Our work approximate topological changes

Our Work: Approximate Topological Changes

time of contact

time of contact

time of separation

time of contact


Main results

Main Results

  • Detect topology changes of free space using

    • time of contact: based on conservative advancement for objects with non-linear motions

    • time of separation: based on penetration depth

  • Maintain high reusability between critical changes

    As a result,

  • A more complete representation of free CT-space than approaches with fixed time resolution

  • Significant improvements on efficiency (at least one order of magnitude faster) observed in our experiments


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