A New Solution for Inverse Kinematics of 7-DOF Manipulator Based on Genetic Algorithm

Yang, Yugui; Peng, Guangzheng; Wang, Yifeng; Zhang, Hongli

doi:10.1109/ical.2007.4338892

Cited by 30 publications

(15 citation statements)

References 7 publications

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“…Here, we can observe that the conventional method reported smooth joint displacement in both manipulators as well. Figure 8 reports the path tracking and the position error results for the dual-arm KUKA Youbot system on the circle trajectory using the initial joint configuration in equation (12). The tracking results for manipulator A of the proposed approach p 1 a e matches with the desired trajectory p Ã a e , as well as the conventional method p 2 a e , see Figure 8(a).…”

Section: Cooperative Path Tracking Testsmentioning

confidence: 87%

“…For the other points in the trajectory, the proposed approach Figure 8. Tracking and position error results for KUKA Youbot arms on sinusoidal trajectory using the initial joint configuration (equation (12)). (a) and (b) show the tracking results, where (p 1 ae , p 1 be ) and (p 2 ae , p 2 be ) are the results for the proposed approach and the conventional method, respectively.…”

Section: Cooperative Path Tracking Testsmentioning

confidence: 99%

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Dual-arm cooperative manipulation based on differential evolution

Hernández-Barragán

López-Franco

Alanis

et al. 2019

International Journal of Advanced Robotic Systems

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Cooperative manipulation in dual-arm robotic systems is a fundamental capability to perform many problems such as human-like tasks. In this article, we present an approach to solve dual-arm cooperative manipulation tasks using the differential evolution algorithm. In this work, manipulator kinematics are represented using the Denavit-Hartenberg model. The proposed method is able to avoid singularities because it does not require the inversion of any Jacobian matrix. In addition, the proposed approach handles joint limit constraints based on penalty functions. As a final remark, this approach is suitable for robotic systems of redundant or non-redundant serial manipulators composed of revolute or prismatic joints. Simulation experiments illustrate the effectiveness of the proposed approach under different dual-arm configurations. Furthermore, real experiments were performed using a dual-arm KUKA Youbot system to show the applicability of the proposed approach.

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Section: Cooperative Path Tracking Testsmentioning

confidence: 87%

Section: Cooperative Path Tracking Testsmentioning

confidence: 99%

Dual-arm cooperative manipulation based on differential evolution

Hernández-Barragán

López-Franco

Alanis

et al. 2019

International Journal of Advanced Robotic Systems

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show abstract

“…Nonetheless, binary coding of real parameters introduces accuracy errors not suitable for complex manipulation tasks. Therefore, in [12], a real-coded genetic algorithm was suggested to solve the inverse kinematics problem of a redundant 7-DOF robot manipulator with good accuracy results. Furthermore, realcoded evolutionary algorithms combined with niching and clustering methods have also proved to be effective in finding the multiple solutions of the inverse kinematics problem of modular robot manipulators [19].…”

Section: Related Workmentioning

confidence: 99%

“…This objective function has been usually defined as the end-effector Euclidean pose error; but also energy, joint displacement, and obstacle avoidance have been used as optimization criteria. Several optimization schemes have been proposed to solve this non-linear programming problem, including gradientbased methods [5], heuristic direct-search methods [6], artificial neural networks [7]- [9], and evolutionary algorithms [10]- [12].…”

Section: Introductionmentioning

confidence: 99%

A memetic approach to the inverse kinematics problem

González

Blanco

Moreno

2012

2012 IEEE International Conference on Mechatronics and Automation

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Solving the inverse kinematics problem is at the core of the kinematics control of any articulated mechanism. It refers to determine the joint configuration that places the end-effector in an arbitrary position and orientation in the workspace. Kinematic inversion algorithms are generally based on the (pseudo)inverse Jacobian matrix, however, these methods are local and unstable in the vicinity of singular joint configurations. Alternatively, the inverse kinematics can be formulated as a constrained minimization problem in the robot configuration space. In a previous work, Differential Evolution (DE) was used to solve this optimization problem for a non-redundant robot manipulator. Although, the algorithm was successful in finding accurate solutions it showed a low convergence speed rate. In this paper, a memetic approach is proposed to increase the convergence speed of the DE by introducing a local search mechanism, called discarding. The proposed approach is tested in a simulation environment to solve the kinematic inversion problem of a non-redundant 3DOF robot manipulator. Experimental results shows that the proposed algorithm is able to find solutions with high accuracy in less generations than the original DE approach.

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“…Genetic algorithms have already been used in many kinematic problems [21,22]. The genetic algorithm performs an exhaustive exploration of the solution space in order find a solution.…”

Section: Solver Implementationmentioning

confidence: 99%

Design of Non-Anthropomorphic Robotic Hands for Anthropomorphic Tasks

Simo-Serra

Moreno-Noguer

Pérez-Gracia

2011

Volume 6: 35th Mechanisms and Robotics Conference, Parts a and B

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In this paper, we explore the idea of designing nonanthropomorphic multi-fingered robotic hands for tasks that replicate the motion of the human hand. Taking as input data a finite set of rigid-body positions for the five fingertips INTRODUCTIONThere are many applications for which a robotic system is needed to work in human environments and to perform tasks that are designed for the human hand. In most cases, the solution adopted for grasping and manipulation consists of anthropomorphic robotic hands, which imitate to a certain extent the topology and joint location of the human hand. See [1] for a review of applications and concept definition.It is difficult to match the complexity of the human hand, commonly accepted to have 26 degrees of freedom when counting the motion at the wrist and the pronation/supination of the forearm. The anthropomorphic design must include a complex mechanical system, actuation and sensing in a small space [2]. In order to reduce complexity, current designs limit the active degrees of freedom, through simplification of the mechanical structure or by designing underactuated hands. The design of simplified grippers limits the tasks of the robotic end-effector to some grasping and manipulation actions. Pairing these designs with some degree of underactuation and compliance, it is then possible to perform robust grasping of objects of unknown shape. Dollar and Howe [3] present a simplified, underactuated design for reliable grasping. Ciocarlie and Allen [4] optimize an underactuated, non-anthropomorphic gripper for performing a series of grasps from a database. A more thorough review on underactuated hands can be found in [5].In order to perform some of the more complex functions

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A New Solution for Inverse Kinematics of 7-DOF Manipulator Based on Genetic Algorithm

Cited by 30 publications

References 7 publications

Dual-arm cooperative manipulation based on differential evolution

Dual-arm cooperative manipulation based on differential evolution

A memetic approach to the inverse kinematics problem

Design of Non-Anthropomorphic Robotic Hands for Anthropomorphic Tasks

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