Trajectory Planning in Time Augmented C-space Using RRT with Sampling Point Including Velocity Determined by Initial Conditions

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

1 Citation (Scopus)

Abstract

The introduction of collaborative robots is expected as one of the solutions for the labor shortage. To implement the collaborative robot in an industrial line, real-time motion planning is necessary to determine a robot's trajectory in order to consider the moving workers. In this paper, we propose a real-time trajectory planning method for co-worker robot based on the RRT in configuration-time space. Motion planning in configuration-time space is effective to avoid moving obstacles while considering robot dynamics and target reach time. In order to consider the dynamics of a robot in a time augmented configuration space, it is necessary to smoothly connect the robot velocities. The proposed method set the velocity of the sampling points depending on the initial condition in configuration-time space. In the simulation, we found that the proposed method has a higher success rate than the method without considering the velocity of the sampling points. Experiments using PaDY that we have developed show the effectiveness of the proposed method in an environment with two moving workers.

Original languageEnglish
Title of host publicationProceedings of the 2020 IEEE/SICE International Symposium on System Integration, SII 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages170-175
Number of pages6
ISBN (Electronic)9781728166674
DOIs
Publication statusPublished - 2020 Jan
Event2020 IEEE/SICE International Symposium on System Integration, SII 2020 - Honolulu, United States
Duration: 2020 Jan 122020 Jan 15

Publication series

NameProceedings of the 2020 IEEE/SICE International Symposium on System Integration, SII 2020

Conference

Conference2020 IEEE/SICE International Symposium on System Integration, SII 2020
CountryUnited States
CityHonolulu
Period20/1/1220/1/15

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Biomedical Engineering
  • Control and Systems Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization
  • Instrumentation

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