A Novel Method for Inverse Kinematics Solutions of Space Modular Self-Reconfigurable Satellites with Self-Collision Avoidance

An, Jiping; Li, Xinhong; Zhang, Zhibin; Zhang, Guohui; Man, Wanxin; Hu, Gangxuan; He, Junwei; Yu, Dingzhan

doi:10.3390/aerospace9030123

Cited by 3 publications

(2 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Space Engineering University proposes to connect multiple modular satellites by mechanical joints to form a modular self-reconfigurable satellite [16], as shown in Figure 1. The satellite module is connected to the robotic arm through a standardized interface.…”

Section: Introductionmentioning

confidence: 99%

“…The optimization method is based on positive kinematic equations and does not suffer from joint singularities. When additional constraints are added to the multi-solution inverse kinematics, the optimal solutions for different objectives can be obtained [16]. The swarm intelligence optimization algorithm has been widely used in inverse kinematics, including particle swarm algorithm [17], clone selection algorithm, firefly algorithm, etc.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Modular Self-Reconfigurable Satellite Inverse Kinematic Solution Method Based on Improved Differential Evolutionary Algorithm

Zhang²,

Li³

et al. 2022

Aerospace

Self Cite

View full text Add to dashboard Cite

The modular self-reconfigurable satellites (MSRSs) are a new type of satellite that can transform configuration in orbit autonomously. The inverse kinematics of MSRS is difficult to solve by conventional methods due to the hyper-redundant degrees of freedom. In this paper, the kinematic model of the MSRS is established, and the inverse kinematic of the MSRS is transformed into an optimal solution problem with minimum pose error and minimum energy consumption. In order to find the inverse kinematic exact solution, the refractive opposition-based learning and Cauchy mutation perturbation improved differential evolutionary algorithm (RCDE) is proposed. The performance of the algorithm was examined using benchmark functions, and it was demonstrated that the accuracy and convergence speed of the algorithm were significantly improved. Three typical cases are designed, and the results demonstrate that the optimization method is effective in solving the MSRS inverse kinematics problem.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modular Self-Reconfigurable Satellite Inverse Kinematic Solution Method Based on Improved Differential Evolutionary Algorithm

Zhang²,

Li³

et al. 2022

Aerospace

Self Cite

View full text Add to dashboard Cite

show abstract

Design of artificial neural networks optimized through genetic algorithms and sequential quadratic programming for tuberculosis model

Shoaib

Kainat

Raja

et al. 2022

Waves in Random and Complex Media

View full text Add to dashboard Cite

Hybrid-Flash Butterfly Optimization Algorithm with Logistic Mapping for Solving the Engineering Constrained Optimization Problems

Zhang

Wang

Yang

2022

Entropy

View full text Add to dashboard Cite

Only the smell perception rule is considered in the butterfly optimization algorithm (BOA), which is prone to falling into a local optimum. Compared with the original BOA, an extra operator, i.e., color perception rule, is incorporated into the proposed hybrid-flash butterfly optimization algorithm (HFBOA), which makes it more in line with the actual foraging characteristics of butterflies in nature. Besides, updating the strategy of the control parameters by the logistic mapping is used in the HFBOA for enhancing the global optimal ability. The performance of the proposed method was verified by twelve benchmark functions, where the comparison experiment results show that the HFBOA converges quicker and has better stability for numerical optimization problems, which are compared with six state-of-the-art optimization methods. Additionally, the proposed HFBOA is successfully applied to six engineering constrained optimization problems (i.e., tubular column design, tension/compression spring design, cantilever beam design, etc.). The simulation results reveal that the proposed approach demonstrates superior performance in solving complex real-world engineering constrained tasks.

show abstract

A Novel Method for Inverse Kinematics Solutions of Space Modular Self-Reconfigurable Satellites with Self-Collision Avoidance

Cited by 3 publications

References 37 publications

Modular Self-Reconfigurable Satellite Inverse Kinematic Solution Method Based on Improved Differential Evolutionary Algorithm

Modular Self-Reconfigurable Satellite Inverse Kinematic Solution Method Based on Improved Differential Evolutionary Algorithm

Design of artificial neural networks optimized through genetic algorithms and sequential quadratic programming for tuberculosis model

Hybrid-Flash Butterfly Optimization Algorithm with Logistic Mapping for Solving the Engineering Constrained Optimization Problems

Contact Info

Product

Resources

About