Kinematics and trajectory planning analysis based on hybrid optimization algorithms for an industrial robotic manipulators
نویسندگان
چکیده
In industrial applications and automation, the robotic manipulators exhibit a significant role. Several complex systems performed number of works named spray painting, welding, assembly, pick place action, etc. The end-effector’s position joint angles play vital role since any task is activated inside pre-defined manipulator’s work space. Also, problem trajectory planning very challenging in fields. To solve these problems, this paper proposes kinematics analysis an Industrial (IRMs) based on hybrid optimization algorithms. Here, three IRMs such as PUMA 560 (6 DOF), KUKA LBR iiwa 14 R820 (7DOF) ABB IRB 140 (6DOF) are considered. For each robot, forward inverse (IK) analysed also robot discussed using work, 18 algorithms PSO (particle swarm optimization), SSO (social spider DFO (dragonfly BOA (butterfly CSA (crow search algorithm), BSA (bird SHO (selfish herd KHO (krill ALO (antlion ACO (ant colony GWO (Grey wolf GOA (grasshopper SBO (satin bowerbird optimizer), WCO (world cup COA (cuckoo CFA (cuttlefish SOA (seagull TSA (tunicate algorithm) utilized for both kinematic problem. 560, R820, IRMs, (FK) solved by combination PSO-SSO, SHO-KHO, SBO-WCO individually. IK DFO-BOA, ALO-ACO COA-CFA IRMs. CSA-BSA, GWO-GOA SOA-TSA These techniques give solution but it converses best minimum multi-objective function value. Each obtained travelling time without with obstacle which 0.0118 0.0313 s 0.0117 0.0310 KUKA, 0.0114 0.0120 robot. advantages algorithm shorter computation time, fewer iterations. IRM simulated tool box MATLAB GUI interface. IRM, optimized values end effector, optimal path computed objective function. Finally, performance compared to existing works.
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ژورنال
عنوان ژورنال: Soft Computing
سال: 2022
ISSN: ['1433-7479', '1432-7643']
DOI: https://doi.org/10.1007/s00500-022-07423-y