Workspace analysis and optimal design of dual cable-suspended robots for construction

Qin, Zhiwei; Liu, Zhen; Liu, Yafang; Gao, Haibo; Sun, Cong; Sun, Guangming

doi:10.1016/j.mechmachtheory.2022.104763

Cited by 14 publications

(3 citation statements)

References 21 publications

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“…Where k is the number of iterations, in (9) D represent the distance between the prey X p (k) and the i wolf X i (k), with i = 1, ..., N . For the wolf next position, (10), A and C are coefficient vectors. The vector A conditions the hunting of the prey (A > 1) and its search (A < 1).…”

Section: F Grey Wolf Optimizermentioning

confidence: 99%

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Kinematic Optimization of 6DOF Serial Robot Arms by Bio-Inspired Algorithms

Galan-Uribe¹,

Morales-Velazquez²

2022

IEEE Access

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Robotic systems are essential to technological development in the industrial, medical, and aerospace sectors. Nevertheless, their use in different applications requires that the robot have the best possible execution efficiency. For this, a robot with specific optimized characteristics is necessary to impact the performance of the specific task. Different techniques have been used in robot optimization, the most widely used being genetic algorithms (GA) and particle swarm optimization (PSO). However, there are optimization algorithms with high convergence speeds inspired by animal behavior, whose application in robot optimization has not been reported. In this work, bio-inspired algorithms Harris hawks optimization (HHO) and Grey wolf optimizer (GWO) are applied to a six-degree-of-freedom (6DOF) robot arm design through kinematic optimization. The lengths of the main robot links are optimized to improve the workspace volume and obtain a better-conditioned robot using the structural length index (SLI) and global condition index (GCI) as objective functions. A comparison is made between the proposed algorithms and GA and PSO regarding convergence speed, computational load, and optimality. Similar behavior has been found for HHO, GWO, and PSO compared to GA for both indexes. For the GCI problem, an average improvement of 14% was found when optimizing an industrial robot arm. Furthermore, multiple runs experiment is performed to test the robustness of the algorithms. The results show that HHO is the best technique to obtain an optimal robot design because it needs less than ten iterations to provide a better result despite its computational load.INDEX TERMS Evolutionary computation, genetic algorithms, grey wolf optimizer, harris hawk optimizer, particle swarm optimization, robot kinematics.

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Section: F Grey Wolf Optimizermentioning

confidence: 99%

“…Another example is [9], which optimizes the mechanical parameters of a wearable robotic limb for hemiplegia rehabilitation, meeting the requirement to be used for humans. Finally, in [10], the design variables of a dual cablesuspended robot for construction are optimized to avoid collisions and obtain a sizeable free-collision workspace.…”

Section: Introductionmentioning

confidence: 99%

Kinematic Optimization of 6DOF Serial Robot Arms by Bio-Inspired Algorithms

Galan-Uribe¹,

Morales-Velazquez²

2022

IEEE Access

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“…By installing different work tools on the end-effector, this robot can be applied to different work scenarios. Currently, it is widely used in medical, aviation, and building cleaning scenarios [8][9][10]. Chen [11] proposed that CDPRs be applied to the field of human lumbar rehabilitation, which can assist in achieving lumbar extension and bending movements.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Modeling and Motion Control Strategy of Cable-Driven Cleaning Robot for Ship Cargo Hold

Han

Chen

et al. 2023

JMSE

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Ship cargo-hold cleaning is a low-efficiency and high-risk operation in marine industry, which is generally carried out manually, putting the workers in danger. To improve the efficiency and safety of ship cargo-hold cleaning, a C-DCR is proposed in this article. Most research on the dynamics and control of CDPRs has focused on the scenarios with fixed bases; however, the effect of moving-base excitation on the end-effector is largely ignored. In this article, the dynamic model is established based on Lagrange method considering the ship motion and external disturbance, in which the motor model is considered. On this basis, for the high-speed maneuverability of the C-DCR, a modified PD feedforward tracking controller was proposed. Furthermore, the stability of the controller was proved with the Lyapunov Stability Theory. To keep the cable in tension at all times, the tensions are optimized based on the minimum 2-norm method. The simulation results show that the error mean of position is 0.22 m and the angular error mean is 2.8° under ship motion and external disturbance, indicating that the C-DCR has stable, smooth and bounded tracking performance, which will ensure the accuracy of the cleaning operation.

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