Abstract | ||
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This paper first reviews heuristic-based and bio-inspired contributions in inverse kinematics. A new inverse kinematics solver is then proposed based on beta distributed Salp Swarm Algorithm called β-SSA. The proposed algorithm is an alternative of the SSA algorithm where leading salps are distributed based on the beta function, enabling a better control of their repartition on the search space. The $$\beta$$ -SSA inverse kinematics solver is named IK- $$\beta$$ -SSA and can be considered as a generic framework. It uses a generic formulation of a forward kinematic model of a robotic system to retrieve its inverse solution. Inverse solution consists in obtaining a possible and feasible joint motions allow the robotic system to achieve a specific position while satisfying intrinsic constraints such as joints positions/ velocities limitations or path limitations. The $$\beta$$ -SSA algorithm is first tested on a set of test functions and compared to nominal SSA prior to be applied to solve the inverse kinematics problem of the industrial robotic arm, Kuka Kr05-arc. The proposed method shows very competitive results when compared to classical SSA, QPSO, Bi-PSO, K-ABC and FA. The experimental results based on simulations and a Wilcoxon non-parametric statistical tests evidently show that the $$IK-\beta$$ -SSA performs better than classical SSA, QPSO, Bi-PSO, K-ABC and FA for a single point inverse kinematics solution using a generic 8 Dof arm and the Kr05 industrial robot. For the path planning, a circular path tracking was investigated using the Kr05 robot and confirmed also that the $$\beta$$ -SSA performs better than classical SSA, QPSO, Bi-PSO, K-ABC and FA. |
Year | DOI | Venue |
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2022 | 10.1007/s10489-021-02831-3 | Applied Intelligence |
Keywords | DocType | Volume |
Meta-heuristics, Salp swarm algorithm, Beta distributed SSA, Inverse kinematics, Optimization | Journal | 52 |
Issue | ISSN | Citations |
9 | 0924-669X | 0 |
PageRank | References | Authors |
0.34 | 30 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Rokbani, Nizar | 1 | 0 | 0.34 |
Seyedali Mirjalili | 2 | 3949 | 140.80 |
Slim, Mohamed | 3 | 0 | 0.34 |
Mohamed Adel Alimi | 4 | 1947 | 217.16 |