Synthesis of Trajectory Planning Algorithms Using Evolutionary Optimization Algorithms

Malyshev, Dmitry; Cherkasov, V. V.; Rybak, Larisa; Diveev, Askhat

doi:10.1007/978-3-031-22990-9_11

Cited by 4 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As an optimization algorithm, we use a parallel modification of the PSO algorithm [32], which has successfully proven itself for solving a wide range of optimization problems.…”

Section: Selection Of Optimization Criterionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Design of Lower Limb Rehabilitation System Based on Parallel and Serial Mechanisms

Malyshev,

Perevuznik,

Ceccarelli

2024

Machines

View full text Add to dashboard Cite

This paper presents the structure and model of a hybrid modular structure of a robotic system for lower limb rehabilitation. It is made of two modules identical in structure, including an active 3-PRRR manipulator for moving the patient’s foot and a passive orthosis based on the RRR mechanism for supporting the lower limb. A mathematical model has been developed to describe the positions for the links of the active and passive mechanisms of two modules, as a function of the angles in the joints of the passive orthosis, considering constraints for attaching the active manipulators to the moving platform and their configurations. A method has been formulated for a parametric synthesis of the hybrid robotic system proposed with modular structure, taking into account the generated levels of parametric constraints depending on the ergonomic and manufacturability features. The proposed design is based on a criterion in the form of a convolution, including two components, one of which is based on minimizing unattainable points of the trajectory, considering the characteristics of anthropometric data, and the other is based on the compactness of the design. The results of the mathematical modeling are discussed as well as the analysis results towards a prototype validation.

show abstract

“…As an optimization algorithm, we use a parallel modification of the PSO algorithm [32], which has successfully proven itself for solving a wide range of optimization problems.…”

Section: Selection Of Optimization Criterionmentioning

confidence: 99%

“…Iterative optimization was performed. Iterative computations are worked out to obtain optimal solutions using the PSO (Particle Swarm Optimization) algorithm [32]. Each iteration is performed independently of each other to obtain results at different local minima.…”

Section: Constraint Levelmentioning

confidence: 99%