An Optimization Method for Dual-arm Robot Task Scheduling Considering Collision Risk

An optimization method is presented for dual-arm robot task scheduling in this paper. The purpose of task scheduling is to assign tasks and determine optimal task paths for dual-arm robot. The robot tasks are considered as a set of task points. The task scheduling is modeled as a Multi-Objective Mul...

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Bibliographic Details
Published in2022 China Automation Congress (CAC) pp. 5402 - 5406
Main Authors Chen, Zixuan, Yuan, Xianzhe, Gu, Qiang, Hu, Chunxu, He, Dingxin
Format Conference Proceeding
LanguageEnglish
Published IEEE 25.11.2022
Subjects
Collision avoidance
collision risk
dual-arm robot
genetic algorithm
Manipulators
Optimization methods
path planning
Planning
Safety
Task analysis
task scheduling
Traveling salesman problems
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Summary:An optimization method is presented for dual-arm robot task scheduling in this paper. The purpose of task scheduling is to assign tasks and determine optimal task paths for dual-arm robot. The robot tasks are considered as a set of task points. The task scheduling is modeled as a Multi-Objective Multiple Traveling Salesman Problem (MOMTSP) to optimize three goals (total time consumption, takt time and collision risk). An improved algorithm based on Non-dominated Sorting Genetic Algorithm (NSGA-II) is proposed for the MOMTSP solution. The simulation demonstrates that the improved algorithm performs faster iterations and better results. Experimental results are shown to prove the method improvement compared with the classical method based on genetic algorithm. The proposed method significantly reduces the collision risk and time consumption.
ISSN:2688-0938
DOI:10.1109/CAC57257.2022.10054947