3-RSS/S Parallel Robot Modeling And Co-Simulation

Abstract We present extensions to ChainQueen, an open source, fully differentiable material point method simulator for soft robotics. Previous work established ChainQueen as a powerful tool for inference, control, and co-design for soft robotics. We detail enhancements to ChainQueen, allowing for more efficient simulation and optimization and expressive co-optimization over material properties and geometric parameters. We package our simulator extensions in an easy-to-use, modular application programming interface (API) with predefined observation models, controllers, actuators, optimizers, and geometric processing tools, making it simple to prototype complex experiments in 50 lines or fewer. We demonstrate the power of our simulator extensions in over nine simulated experiments.

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Sensitivity Based Selection of an Optimal Cable-Driven Parallel Robot Design for Rehabilitation Purposes

Robotics ◽

10.3390/robotics10010007 ◽

2020 ◽

Vol 10 (1) ◽

pp. 7

Author(s):

Ferdaws Ennaiem ◽

Abdelbadiâ Chaker ◽

Juan Sebastián Sandoval Arévalo ◽

Med Amine Laribi ◽

Sami Bennour ◽

...

Keyword(s):

Pareto Front ◽

Parallel Robot ◽

Elastic Stiffness ◽

Upper Limb Rehabilitation ◽

Daily Life Activities ◽

System A ◽

The Monte Carlo Method ◽

Genetic Algorithm Method ◽

Limb Rehabilitation ◽

Selection Of

This paper deals with the design of an optimal cable-driven parallel robot (CDPR) for upper limb rehabilitation. The robot’s prescribed workspace is identified with the help of an occupational therapist based on three selected daily life activities, which are tracked using a Qualisys motion capture system. A preliminary architecture of the robot is proposed based on the analysis of the tracked trajectories of all the activities. A multi-objective optimization process using the genetic algorithm method is then performed, where the cable tensions and the robot size are selected as the objective functions to be minimized. The cables tensions are bounded between two limits, where the lower limit ensures a positive tension in the cables at all times and the upper limit represents the maximum torque of the motor. A sensitivity analysis is then performed using the Monte Carlo method to yield the optimal design selected out of the non-dominated solutions, forming the obtained Pareto front. The robot with the highest robustness toward the disturbances is identified, and its dexterity and elastic stiffness are calculated to investigate its performance.

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A comparative study of two inverse dynamic models of 6 degree-of-freedom rotary Stewart-Gough parallel robot

International Journal of Dynamics and Control ◽

10.1007/s40435-021-00820-5 ◽

2021 ◽

Author(s):

Zafer Mahmoud ◽

Mohammad Reza Arvan ◽

Vahab Nekoukar ◽

Mohammad Rezaei

Keyword(s):

Comparative Study ◽

Dynamic Models ◽

Parallel Robot ◽

Degree Of Freedom ◽

Inverse Dynamic

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Social spider optimization algorithm for tuning parameters in PD-like Interval Type-2 Fuzzy Logic Controller applied to a parallel robot

Measurement and Control ◽

10.1177/0020294021997483 ◽

2021 ◽

Vol 54 (3-4) ◽

pp. 303-323

Author(s):

Amjad J Humaidi ◽

Huda T Najem ◽

Ayad Q Al-Dujaili ◽

Daniel A Pereira ◽

Ibraheem Kasim Ibraheem ◽

...

Keyword(s):

Fuzzy Logic ◽

Trajectory Tracking ◽

Fuzzy Logic Controller ◽

Optimization Technique ◽

Parallel Robot ◽

Design Parameters ◽

Social Spider ◽

Social Spider Optimization ◽

Interval Type

This paper presents control design based on an Interval Type-2 Fuzzy Logic (IT2FL) for the trajectory tracking of 3-RRR (3-Revolute-Revolute-Revolute) planar parallel robot. The design of Type-1 Fuzzy Logic Controller (T1FLC) is also considered for the purpose of comparison with the IT2FLC in terms of robustness and trajectory tracking characteristics. The scaling factors in the output and input of T1FL and IT2FL controllers play a vital role in improving the performance of the closed-loop system. However, using trial-and-error procedure for tuning these design parameters is exhaustive and hence an optimization technique is applied to achieve their optimal values and to reach an improved performance. In this study, Social Spider Optimization (SSO) algorithm is proposed as a useful tool to tune the parameters of proportional-derivative (PD) versions of both IT2FLC and T1FLC. Two scenarios, based on two square desired trajectories (with and without disturbance), have been tested to evaluate the tracking performance and robustness characteristics of proposed controllers. The effectiveness of controllers have been verified via numerical simulations based on MATLAB/SIMULINK programming software, which showed the superior of IT2FLC in terms of robustness and tracking errors.

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