Time-based RRT algorithm for rendezvous planning of two dynamic systems

Avishai Sintov, Amir Shapiro

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Scopus citations

Abstract

The work presented in this paper proposes a new method for time based motion planning of a dynamic system to reach a dynamical goal within a specified time. The method enables trajectory planning based on the dynamics of the system with time constraint. Moreover, this method allows rendezvous planning of two dynamic systems where only one is controlled. To reach this objective, we introduce a new concept termed Time-Based RRT (TB-RRT) which is an extended version of the Rapidly-exploring Random Tree (RRT). The concept of the TB-RRT is to add time parameters to the nodes in the tree such that each node denotes a specific state in a specific time. The algorithm was implemented in two applications to demonstrate the approach and validate its feasibility; The first application is a one degree of freedom bat hitting a ball and the second application is a three degrees of freedom manipulator catching a moving object. Simulation results show the system accurately following the planned trajectory and the robot catching the object in time.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Robotics and Automation
PublisherInstitute of Electrical and Electronics Engineers
Pages6745-6750
Number of pages6
ISBN (Electronic)9781479936854, 9781479936854
DOIs
StatePublished - 22 Sep 2014
Event2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China
Duration: 31 May 20147 Jun 2014

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2014 IEEE International Conference on Robotics and Automation, ICRA 2014
Country/TerritoryChina
CityHong Kong
Period31/05/147/06/14

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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