Optimal three dimensional robot path planning with collision avoidance

Piyush K. Jain, Souran Manoochehri

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

Abstract

The study reported in this paper deals with path planning in three-dimensional space using network optimization for robotic manipulators working in the presence of obstacles and workspace singularities. To execute the algorithm, the robot design parameters, the geometry and location of the obstacles, and the initial and goal positions of the desired task are required. As a first step, the manipulator workspace is discretized and points inside forbidden regions formed by obstacles and singularities are excluded. An ellipsoidal searchspace is then selected as a part of the workspace to make the network enumeration and path synthesis more efficient. Based on an allowable deviation angle, path segments are created to form the connectivity network. A path which is optimal with respect to the manipulator kinematic and dynamic properties is generated as a sequence of intermediate points connecting the initial and goal states using Dijkstra's minimum cost search technique. A computer program has been developed to implement this methodology for three-axis manipulators, and results of the application of this algorithm to some industrial robots are presented.

Original languageEnglish
Title of host publicationFinite Elements/Computational Geometry; Computers in Education; Robotics and Controls
Pages493-500
Number of pages8
ISBN (Electronic)9780791806234, 9780791897768
DOIs
StatePublished - 1991
EventASME 1991 Design Technical Conferences, DETC 1991 - Miami, United States
Duration: 22 Sep 199125 Sep 1991

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume2

Conference

ConferenceASME 1991 Design Technical Conferences, DETC 1991
Country/TerritoryUnited States
CityMiami
Period22/09/9125/09/91

Fingerprint

Dive into the research topics of 'Optimal three dimensional robot path planning with collision avoidance'. Together they form a unique fingerprint.

Cite this