Optimal kinematic design of a single-DOF planar grasper based on metaheuristic optimization
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A method is proposed for optimal synthesis of a grasper mechanism for circular objects. A single-DOF linkage-type grasper is developed considering the geometry of the target objects. The mechanism consists of successive coupled four-bar linkages and is capable of grasping circular objects with desirable range of diameter. The synthesis problem is formulated as a constraint optimization problem, while adaptive inertia weight particle swarm optimization (AIW-PSO) approach is used to carry out the solutions. Biomechanical and industrial applications for the mechanism are suggested and investigated by simulations as case studies. To demonstrate the effectiveness of AIW-PSO on the problem, a comparison with two other well-known metaheuristic algorithms namely PSO and genetic algorithm is done. The results show the efficiency of the proposed algorithm and the performance of the mechanism.
KeywordsOptimal design Mechanism design Adaptive PSO Nature-inspired Optimization Grasp
We are grateful to Mr. Mohammad Reza Manaberi for providing us the 3D model of the linkage.
- 3.Yamaguchi K, Hirata Y, Kaisumi A, Kosuge K (2012) Design of parts handling and gear assembling device. In: Paper presented at the 2012 IEEE international conference on robotics and automation (ICRA)Google Scholar
- 8.Sintov A, Menassa RJ, Shapiro A (2016) A gripper design algorithm for grasping a set of parts in manufacturing lines. Mech Mach Theory 105:1–30. https://doi.org/10.1016/j.mechmachtheory.2016.06.015 CrossRefGoogle Scholar
- 10.Sumi S, Böhm V, Zimmermann K (2017) A multistable tensegrity structure with a gripper application. Mech Mach Theory 114:204–217. https://doi.org/10.1016/j.mechmachtheory.2017.04.005 CrossRefGoogle Scholar
- 13.Stavenuiter RA, Birglen L, Herder JL (2017) A planar underactuated grasper with adjustable compliance. Mech Mach Theory 112:295–306. https://doi.org/10.1016/j.mechmachtheory.2016.08.001 CrossRefGoogle Scholar
- 14.Rodríguez NEN, Carbone G, Ceccarelli M (2006) Optimal design of driving mechanism in a 1-DOF anthropomorphic finger. Mech Mach Theory 41(8):897–911. https://doi.org/10.1016/j.mechmachtheory.2006.03.016 CrossRefzbMATHGoogle Scholar
- 18.Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Paper presented at the Proceedings of the 1995 IEEE international conference on neural networksGoogle Scholar
- 20.Lei K, Qiu Y, He Y (2006) A new adaptive well-chosen inertia weight strategy to automatically harmonize global and local search ability in particle swarm optimization. In: 2006. ISSCAA 2006. 1st international symposium on paper presented at the systems and control in aerospace and astronauticsGoogle Scholar
- 22.Saber AY, Senjyu T, Urasaki N, Funabashi T (2006) Unit commitment computation-a novel fuzzy adaptive particle swarm optimization approach. In: Paper presented at the power systems conference and exposition, 2006. PSCE’06. 2006 IEEE PESGoogle Scholar
- 25.Bataller A, Cabrera J, Clavijo M, Castillo J (2016) Evolutionary synthesis of mechanisms applied to the design of an exoskeleton for finger rehabilitation. Mech Mach Theory 105:31–43. https://doi.org/10.1016/j.mechmachtheory.2016.06.022 CrossRefGoogle Scholar