DocumentCode :
2045075
Title :
Multi-objective trajectory optimization for space manipulator with multi-constraints
Author :
Yuqiang Liu ; Chunlin Tan ; Hanxu Sun ; Gang Chen
Author_Institution :
Inst. of Spacecraft Syst. Eng., CAST, Beijing, China
fYear :
2015
fDate :
2-5 Aug. 2015
Firstpage :
1542
Lastpage :
1547
Abstract :
In order to improve the motion performance of space manipulators, multiple objectives and constraints are required in operations on orbit. Based on non-dominated sorting genetic algorithm (NSGA-II), a method is proposed to achieve multi-objective trajectory optimization with multi-constraints. Considering the maximum speed and acceleration at the end-effector as decision variables, quantities of operation time and energy cost are treated as optimal goals. Moreover, multi-constraints of manipulator and the environment are introduced during the trajectory optimization. As a result, equations of multi-objective trajectory optimization are established. Then the Pareto optimal set of multi-objective optimization problem (MOP) is calculated, and the validity of the algorithm is verified with a seven degree-of freedom (DOF) space manipulator.
Keywords :
Pareto optimisation; aerospace robotics; genetic algorithms; manipulators; NSGA-II; Pareto optimal set; multiconstraints; multiobjective optimization problem; multiobjective trajectory optimization; nondominated sorting genetic algorithm; seven degree-of freedom; space manipulators; Joints; Manipulators; Optimization; Sociology; Space vehicles; Statistics; Torque; Multi-constraints; Multi-objective; NSGA-II; Space manipulator; Trajectory optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation (ICMA), 2015 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-7097-1
Type :
conf
DOI :
10.1109/ICMA.2015.7237714
Filename :
7237714
Link To Document :
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