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Workspace-Based Approach for Robot Trajectory Evaluation

  • Abhishek Jha
  • , Arjun Rajesh
  • , Ankur Jaiswal*
  • *Corresponding author for this work

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

Abstract

A robot’s workspace refers to the surrounding environment where robot can move, operate, and interact with the other objects for task accomplishment. Analysis of robot workspace is an important aspect in robot’s motion planning, task execution, and interaction with the world. This paper presents a framework to assess the suitability of a given trajectory in the robot workspace. The framework utilizes kinematic modeling along with the adaptive neuro fuzzy inference system to learn the robot workspace model. Afterward, the learned model is used to retrieve an analogous trajectory corresponding to the specified task at the trajectory level. The approach is demonstrated for a six degrees of freedom industrial robot in a simulation environment. Simulation results reflect that the proposed approach provides a simplified way to evaluate the executability of an externally defined trajectory by the robot.

Original languageEnglish
Title of host publicationIntelligent Control, Robotics, and Industrial Automation - Proceedings of International Conference, RCAAI 2023
EditorsShilpa Suresh, Shyam Lal, Mustafa Servet Kiran
PublisherSpringer Science and Business Media Deutschland GmbH
Pages573-584
Number of pages12
ISBN (Print)9789819746491
DOIs
Publication statusPublished - 2024
EventInternational Conference on Robotics, Control, Automation and Artificial Intelligence, RCAAI 2023 - Manipal, India
Duration: 12-10-202314-10-2023

Publication series

NameLecture Notes in Electrical Engineering
Volume1220 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Conference on Robotics, Control, Automation and Artificial Intelligence, RCAAI 2023
Country/TerritoryIndia
CityManipal
Period12-10-2314-10-23

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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