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Liu Y, Du Z, Wu Z, Liu F, Li X. Multiobjective preimpact trajectory planning of space manipulator for self-assembling a heavy payload. INT J ADV ROBOT SYST 2021. [DOI: 10.1177/1729881421990285] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
To assemble a heavy payload to the spacecraft (free-floating base), the present study proposes a scheme of multiobjective trajectory planning for preimpact motion of redundant space manipulator (mounted on the base). Force impulse for self-assembly is derived as the function of joint angles/velocities, base pose, and impact direction. The trajectory planning problem is formulated as multiobjective optimization to minimize force impulse, base attitude disturbance, and energy consumption in the load-carrying process. A two-stage trajectory planning algorithm is proposed. To be specific, at the first stage, multiple desired configurations at the contact point are generated by position-level inverse kinematics with Newton–Raphson iterative method. At the second stage, joint trajectories satisfying joint angle limits and desired motion of the payload are parameterized by coefficients of sinusoidal polynomial functions. Multiobjective particle swarm optimization algorithm is adopted to solve the problem of multiobjective trajectory planning, and screening process is conducted to reserve nondominated solutions in limits of joint torques. The algorithm is implemented to a seven degrees of freedom space manipulator, and the effectiveness of the proposed method is verified by simulation results.
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Affiliation(s)
- Yong Liu
- School of Mechanical Engineering, Hefei University of Technology, Hefei, China
| | - Zhe Du
- School of Mechanical Engineering, Hefei University of Technology, Hefei, China
| | - Zhe Wu
- School of Mechanical Engineering, Hefei University of Technology, Hefei, China
| | - Fei Liu
- School of Mechanical Engineering, Hefei University of Technology, Hefei, China
| | - Xiaojun Li
- School of Mechanical Engineering, Hefei University of Technology, Hefei, China
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Wei XP, Zhang JX, Zhou DS, Zhang Q. Optimal Path Planning for Minimizing Base Disturbance of Space Robot. INT J ADV ROBOT SYST 2016. [DOI: 10.5772/62126] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
The path planning of free-floating space robot in space on-orbit service has been paid more and more attention. The problem is more complicated because of the interaction between the space robot and base. Therefore, it is necessary to minimize the base position and attitude disturbance to improve the path planning of free-floating space robot, reducing the fuel consumption for the position and attitude maintenance. In this paper, a reasonable path planning method to solve the problem is presented, which is feasible and relatively simple. First, the kinematic model of 6 degrees of freedom free-floating space robot is established. And then the joint angles are parameterized using the 7th order polynomial sine functions. The fitness function is defined according to the position and attitude of minimizing base disturbance and constraints of space robot. Furthermore, an improved chaotic particle swarm optimization (ICPSO) is presented. The proposed algorithm is compared with the standard PSO and CPSO algorithm in the literature by the experimental simulation. The simulation results demonstrate that the proposed algorithm is more effective than the two other approaches, such as easy to find the optimal solution, and this method could provide a satisfactory path for the free-floating space robot.
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Affiliation(s)
- Xiao-Peng Wei
- School of Mechanical Engineering, Dalian University of Technology, Dalian, China
| | - Jian-Xia Zhang
- School of Mechanical Engineering, Dalian University of Technology, Dalian, China
| | - Dong-Sheng Zhou
- Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, Dalian University, Dalian, China
| | - Qiang Zhang
- Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, Dalian University, Dalian, China
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Liu Y, Jia Q, Chen G, Sun H, Peng J. Multi-Objective Trajectory Planning of FFSM Carrying a Heavy Payload. INT J ADV ROBOT SYST 2015. [DOI: 10.5772/61235] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Aiming at carrying a heavy payload to a desired pose (including position and orientation), a multi-objective optimization-based approach for maximum-payload trajectory planning of free-floating space manipulators (FFSM) is proposed in this paper. The presented approach corresponds to two typical applications: (i) the manipulator joints attain the desired states; (ii) the inertial pose of the end-effector (pose with respect to the inertial frame) attains the desired values, for which a novel two-stage method is presented. Firstly, for the purpose of reducing computational complexity, dynamics equations are derived using a spatial operator algebra (SOA) method. Secondly, objective functions are defined according to the improvement of load-carrying capacity and pose requirements of the end-effector. Then, the joint trajectories are specified using sinusoidal polynomial functions. Finally, a multi-objective particle optimization (MOPSO) algorithm is employed to obtain a non-dominated solution set, during which process particles that do not satisfy the constraints are eliminated. Simulations are performed for a 7-DOF FFSM, considering three and five objectives for optimization in the two applications, respectively. The results demonstrate that the proposed approach can provide satisfactory joint trajectories and improve load-carrying capacity effectively.
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Affiliation(s)
- Yong Liu
- Beijing University of Posts and Telecommunications, Beijing, China
| | - Qingxuan Jia
- Beijing University of Posts and Telecommunications, Beijing, China
| | - Gang Chen
- Beijing University of Posts and Telecommunications, Beijing, China
| | - Hanxu Sun
- Beijing University of Posts and Telecommunications, Beijing, China
| | - Junjie Peng
- Beijing University of Posts and Telecommunications, Beijing, China
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