Inverse kinematics of a 6 DOF industrial robot manipulator based on bio-inspired multi-objective optimization techniques

Peña, Cristina García-De la; Guzmán, María A.; Cárdenas, Pedro F.

doi:10.1109/ccra.2016.7811428

Cited by 7 publications

(9 citation statements)

References 15 publications

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“…Multi-objective approaches of articulated systems and robotic arms are not popular, while they are more effective and more suitable to handle the difference in dimensions between position and orientation. Pena et al (2016) developed an MO strategy for inverse kinematics for a 6-DOF robotic arm based on The Fast and Elitists Non-Dominated Sorting Genetic Algorithm and the Bacterial Chemotaxis Multi-Objective Algorithm [17]. The multi-objective inverse kinematics, MO-IK, solver was used to optimize a couple of objective functions for position and orientation of the end-effector.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Objective Modified PSO for Inverse Kinematics of a 5-DOF Robotic Arm

et al. 2022

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In this paper, a new modified particle swarm optimization, m-PSO, is proposed, in which the novelty consists of proposing a fitness-based particle swarm optimization algorithm, PSO, which adapts the particles’ behavior rather than the PSO parameters and where particles evolve differently considering their level of optimality. A multi-objective optimization, MO, approach is then built based on m-PSO. In the proposed method, particles with fitness better than the mean local best are only updated toward the global best, while others keep moving in a classical manner. The proposed m-PSO and its multi-objective version MO-m-PSO are then employed to solve the inverse kinematics of a 5-DOF robotic arm which is 3D-printed for educational use. In the MO-m-PSO approach of inverse kinematics, the arm IK problem is formulated as a multi-objective problem searching for an appropriate solution that takes into consideration the end-effector position and orientation with a Pareto front strategy. The IK problem is addressed as the optimization of the end-effector position and orientation based on the forward kinematics model of the systems which is built using the Denavit–Hartenberg approach. Such an approach allows to avoid classical inverse kinematics solvers challenges such as singularities, which may simply harm the existence of an inverse expression. Experimental investigations included the capacity of the proposal to handle random single points in the workspace and also a circular path planning with a specific orientation. The comparative analysis showed that the mono-objective m-PSO is better than the classical PSO, the CSA, and SSA. The multi-objective variants returned accurate results, fair and better solutions compared to multi-objective variants of MO-PSO, MO-JAYA algorithm, and MO-CSA. Even if the proposed method were applied to solve the inverse kinematics of and educational robotics arms for a single point as well as for a geometric shape, it may be transposed to solve related industrial robotized arms withthe only condition of having their forward kinematics model.

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Section: Introductionmentioning

confidence: 99%

A Multi-Objective Modified PSO for Inverse Kinematics of a 5-DOF Robotic Arm

et al. 2022

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“…Xie et al 12 used an improved DE algorithm to find the IK of a manipulator. Pena et al 13 proposed using bioinspired multiobjective optimization techniques to solve the industrial robot IK problem. The Newton-Raphson method has the advantage of a simple calculation process, high efficiency, and high precision, but its optimization result is too dependent on the choice of initial value.…”

Section: Introductionmentioning

confidence: 99%

Research on the inverse kinematics of manipulator using an improved self-adaptive mutation differential evolution algorithm

Zhang

Wang

Gao

2021

International Journal of Advanced Robotic Systems

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To assess the inverse kinematics (IK) of multiple degree-of-freedom (DOF) serial manipulators, this article proposes a method for solving the IK of manipulators using an improved self-adaptive mutation differential evolution (DE) algorithm. First, based on the self-adaptive DE algorithm, a new adaptive mutation operator and adaptive scaling factor are proposed to change the control parameters and differential strategy of the DE algorithm. Then, an error-related weight coefficient of the objective function is proposed to balance the weight of the position error and orientation error in the objective function. Finally, the proposed method is verified by the benchmark function, the 6-DOF and 7-DOF serial manipulator model. Experimental results show that the improvement of the algorithm and improved objective function can significantly improve the accuracy of the IK. For the specified points and random points in the feasible region, the proportion of accuracy meeting the specified requirements is increased by 22.5% and 28.7%, respectively.

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“…Some researchers solved inverse kinematics problem using different methods including interpolation [15,16] and gradient projection [17][18][19], but these methods were restricted to computation speed and error. A number of novel or so called intelligent numerical resolving methods are used for redundant inverse kinematics problem, including quadratic programming (QP), artificial neural networks, quaternion method, online learning algorithm, and genetic algorithm [20][21][22][23][24]. Among these methods, quadratic programming is tractable and has well expansibility to real-time application.…”

Section: Introductionmentioning

confidence: 99%

Discretized Mid‐Value CLVI‐PDNN Based Redundancy Resolution for Single Leg of Quadruped Robot

Rao

Zhang

et al. 2019

Mathematical Problems in Engineering

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The two most important performance indicators of quadruped robot are load capacity and walking speed, and these performance indicators of the whole robot finally reflect on the joint torques and angular velocities. To satisfy different requirements of walking speed and load capacity when quadruped robots implement different tasks, the joint torques and angular velocities need to be balanced with physical constraints of the joints. A single leg with redundant DOF (degree of freedom) could optimize the distribution of joint torques or angular velocities based on different performance requirements. This paper presents a kind of new recurrent neural networks taking joint torques and angular velocities simultaneously into consideration and proposes mid-value CLVI-PDNN to achieve the optimal joint torques and angular velocities with physical constraints of the mechanism as described in our previous paper. Because the continuous mid-value CLVI-PDNN has difficulty in real-time operation because of too much calculation workload, two kinds of methods are proposed to discretize the mid-value CLVI-PDNN for application on computer or digital circuit. The simulation results demonstrate the efficacy of the algorithm proposed in this paper.

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Inverse kinematics of a 6 DOF industrial robot manipulator based on bio-inspired multi-objective optimization techniques

Cited by 7 publications

References 15 publications

A Multi-Objective Modified PSO for Inverse Kinematics of a 5-DOF Robotic Arm

A Multi-Objective Modified PSO for Inverse Kinematics of a 5-DOF Robotic Arm

Research on the inverse kinematics of manipulator using an improved self-adaptive mutation differential evolution algorithm

Discretized Mid‐Value CLVI‐PDNN Based Redundancy Resolution for Single Leg of Quadruped Robot

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