Maximizing the coverage of roadmap graph for optimal motion planning
type: Item
instance of: scholarly article
title: Maximizing the coverage of roadmap graph for optimal motion planning
zbMATH Open document ID: 1407.93266
DOI: 10.1155/2018/9104720
author: Jae-Han Park
author: Tae-Woong Yoon
published in: Complexity
publication date: 2019-02-19T00:00:00Z
review text: Summary: Automated motion-planning technologies for industrial robots are critical for their application to Industry 4.0. Various sampling-based methods have been studied to generate the collision-free motion of articulated industrial robots. Such sampling-based methods provide efficient solutions to complex planning problems, but their limitations hinder the attainment of optimal results. This paper considers a method to obtain the optimal results in the roadmap algorithm that is representative of the sampling-based method. We define the coverage of a graph as a performance index of its optimality as constructed by a sampling-based algorithm and propose an optimization algorithm that can maximize graph coverage in the configuration space. The proposed method was applied to the model of an industrial robot, and the results of the simulation confirm that the roadmap graph obtained by the proposed algorithm can generate results of satisfactory quality in path-finding tests under various conditions.
Mathematics Subject Classification ID: 93C85
Mathematics Subject Classification ID: 68T40
Mathematics Subject Classification ID: 68T20
zbMATH DE Number: 7025054
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2018/9104720
OpenAlex ID: W2899932486
cites work: Q5713497
cites work: Consensus Problems in Networks of Agents With Switching Topology and Time-Delays
cites work: Distributed optimization of multiagent systems in directed networks with time-varying delay
cites work: A Graph-Theoretic Characterization of Perfect Attackability for Secure Design of Distributed Control Systems
cites work: Distributed Optimization Under Adversarial Nodes
cites work: Coordination and Geometric Optimization via Distributed Dynamical Systems
cites work: Unicycle Coverage Control Via Hybrid Modeling
cites work: Distributed Deployment Algorithms for Coverage Improvement in a Network of Wireless Mobile Sensors: Relocation by Virtual Force
cites work: Q3171227
cites work: Distributed asynchronous deterministic and stochastic gradient optimization algorithms
cites work: Constrained optimization via stochastic approximation with a simultaneous perturbation gradient approximation
cites work: Limit load and shakedown analysis of plastic structures under stochastic uncertainty
cites work: Q3618870
cites work: Q5553232
cites work: Dynamical Processes on Complex Networks
cites work: Q3419537
cites work: Volumes of Generalized Unit Balls
description: scientific article; zbMATH DE number 7025054