A novel RRT∗-based algorithm for motion planning in Dynamic environments

Olzhas Adiyatov, Huseyin Atakan Varol

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Citations (Scopus)

Abstract

Sampling-based motion planning has become a powerful framework for solving complex robotic motion-planning tasks. Despite the introduction of a multitude of algorithms, most of these deal with the static case involving non-moving obstacles. In this work, we are extending our memory efficient RRT∗FN algorithm to dynamic scenarios. Specifically, we retain the useful parts of the tree (the data structure storing the motion plan information) after a dynamic obstacle invalidates the solution path. We then employ two greedy heuristics to repair the solution instead of running the whole motion planning process from scratch. We call this new algorithm, RRT∗FN-Dynamic (RRT∗FND). To compare our method to the state-of-the-art motion planners, RRT∗ and RRT∗FN, we conducted an extensive set of benchmark experiments in dynamic environments using two robot models: a non-holonomic mobile robot and an industrial manipulator. The results of these experiments show that RRT∗FND finds the solution path in shorter time in most of the cases and verifies the efficacy of it in dynamic settings.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1416-1421
Number of pages6
ISBN (Electronic)9781509067572
DOIs
Publication statusPublished - Aug 23 2017
Event14th IEEE International Conference on Mechatronics and Automation, ICMA 2017 - Takamatsu, Japan
Duration: Aug 6 2017Aug 9 2017

Conference

Conference14th IEEE International Conference on Mechatronics and Automation, ICMA 2017
CountryJapan
CityTakamatsu
Period8/6/178/9/17

Keywords

  • Dynamic environments
  • Motion planning
  • Path planning
  • Rapidly-exploring random trees
  • Sampling-based methods

ASJC Scopus subject areas

  • Control and Optimization
  • Instrumentation
  • Artificial Intelligence
  • Industrial and Manufacturing Engineering
  • Mechanical Engineering

Fingerprint Dive into the research topics of 'A novel RRT∗-based algorithm for motion planning in Dynamic environments'. Together they form a unique fingerprint.

Cite this