A meta-heuristic proposal for inverse kinematics solution of 7-DOF serial robotic manipulator: quantum behaved particle swarm algorithm

Dereli, Serkan; Köker, Raşit

doi:10.1007/s10462-019-09683-x

Cited by 105 publications

(56 citation statements)

References 27 publications

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“…To demonstrate the superiority and practicability of the BAS algorithm proposed in this paper, we also comparatively present the performance results of the GA, the PSO, the firefly algorithm (FA) [40] and the quantum behaved particle swarm algorithm (QPSO) [41] for the same motion planning problem. PSO and GA algorithms for comparison are from the Matlab (R2017b) function library.…”

Section: ) Comparison With Other Typical Intelligent Algorithmsmentioning

confidence: 99%

Motion Planning of Redundant Manipulator With Variable Joint Velocity Limit Based on Beetle Antennae Search Algorithm

Cheng

et al. 2020

IEEE Access

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Redundant manipulators play important roles in many industrial and service applications by assisting people fulfill heavy and repetitive jobs. However, redundant manipulators are coupled highlynonlinear systems which exert difficulty of redundancy resolution computation. Conventional methods such as pseudo-inverse-based approaches obtain the resolved joint angles from joint velocity level, which may bring about more computational cost and may neglect joint velocity limits. In this work, a motion planning method based on beetle antennae search algorithm (BAS) is proposed for motion planning of redundant manipulators with the variable joint velocity limit. Such proposed work does not need to resolve the velocity kinematics equation as the conventional methods do, and the proposed method can directly deal with the forward kinematics equation to resolve the desired joint angles. The simulation and experiment on the five-link planar manipulator and the Kuka industrial manipulator system demonstrate the efficiency of the proposed method for motion planning of redundant manipulator, and reveal the reliable performance of the BAS algorithm as compared with genetic algorithm (GA), particle swarm optimization (PSO), firefly algorithm(FA) and quantum behaved particle swarm algorithm(QPSO) methods.

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Section: ) Comparison With Other Typical Intelligent Algorithmsmentioning

confidence: 99%

Motion Planning of Redundant Manipulator With Variable Joint Velocity Limit Based on Beetle Antennae Search Algorithm

Cheng

et al. 2020

IEEE Access

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“…Because all the particles move to a defined position, depending on their own velocities. Therefore, each movement results in a new position [35].…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

Simulation based calculation of the inverse kinematics solution of 7-DOF robot manipulator using artificial bee colony algorithm

Dereli

Köker

2019

SN Appl. Sci.

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This paper presents an artificial bee colony algorithm for solving the inverse kinematics of 7-degree-of-freedom robotic arm which has been newly designed and not used in the literature. The kinematics analysis of this manipulator which has an excessive number of joints, is quite complex. In this study, artificial bee colony, which is one of the swarm-based heuristic algorithms, has been used for inverse kinematics solution and its results have been analyzed in terms of position error and calculation time. In order to ensure the accuracy of the algorithm, calculations have been also carried out in 100 different points selected from the workspace of the robot manipulator. The results have been compared with particle swarm optimization, which is another swarm algorithm in terms of position error and computation time. The results obtained by computer simulation clearly show that the artificial bee colony algorithm produces effective results compared with the literature.

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“…He was able to significantly improve accuracy for IK solutions of a 6-DOF mechanism in comparison to pure neural networks. Very recently, Dereli et al [23] proposed a strategy to apply quantum behaved particle swarm optimization for finding IK solutions of a 7-DOF serial robot.…”

Section: Inverse Kinematicsmentioning

confidence: 99%

Efficient Closed-Form Task Space Manipulability for a 7-DOF Serial Robot

Huber

Wollherr

2019

Robotics

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With the increasing demand for robots to react and adapt to unforeseen events, it is essential that a robot preserves agility at all times. While manipulability is a common measure to quantify agility at a given joint configuration, an efficient direct evaluation in task space is usually not possible with conventional methods, especially for redundant robots with an infinite number of Inverse Kinematic solutions. Yet, this is essential for global online optimization of a robot posture. In this work, we derive analytical expressions for a conventional 7-degrees of freedom (7-DOF) serial robot structure, which enable the direct evaluation of manipulability from a reduced task space parametrization. The resulting expressions allow array operation and thus achieve very high computational efficiency with vector-optimized programming languages. This direct and simultaneous calculation of the task space manipulability for large numbers of poses benefits many optimization problems in robotic applications. We show applications in global optimization of robot mounting poses, as well as redundancy resolution with global online optimization w.r.t. manipulability.

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A meta-heuristic proposal for inverse kinematics solution of 7-DOF serial robotic manipulator: quantum behaved particle swarm algorithm

Cited by 105 publications

References 27 publications

Motion Planning of Redundant Manipulator With Variable Joint Velocity Limit Based on Beetle Antennae Search Algorithm

Motion Planning of Redundant Manipulator With Variable Joint Velocity Limit Based on Beetle Antennae Search Algorithm

Simulation based calculation of the inverse kinematics solution of 7-DOF robot manipulator using artificial bee colony algorithm

Efficient Closed-Form Task Space Manipulability for a 7-DOF Serial Robot

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