In this work, we present a new framework devoted to the numerical solution of nonlinear algebraic systems. The algorithm is composed by a symbiotic organisms search and a repulsion technique. The systematic repetition...
详细信息
In this work, we present a new framework devoted to the numerical solution of nonlinear algebraic systems. The algorithm is composed by a symbiotic organisms search and a repulsion technique. The systematic repetition of a metaheuristic algorithm in order to find the full set of solutions tends to fail since, at times, the same solution is found over and over again. The methodology proposed here, incorporating a repulsion technique, changes the behavior of the symbiotic organisms search, allowing for a better probability of finding a high number of solutions. We tested the methodology in two examples, one of which is the inverse kinematics problem for puma robot. We present a detailed study of the effect that some control parameters have, showing how to increase the probability of identifying more solutions. Overall, the results validate the enhancement attained by the methodology in finding the full set of solutions of the problem.
Economy of motion in robots assembly lines, microelectronics, medical and space applications has not received much attention. It is however, as challenging and important as efficiency and ergonomics is to human beings...
详细信息
Economy of motion in robots assembly lines, microelectronics, medical and space applications has not received much attention. It is however, as challenging and important as efficiency and ergonomics is to human beings in the factory workplace. Production lines with humans are prone to human fatigue. Hence robotic units are replacing human sorters for production line work. Mechanised operations are usually limited to batch processes with identical items taken from a conveyor belt and placed in a bin or stack. A further extension is to use AI programs to enable discrimination of objects and sorting into separate bins or stacks. In the present study a 5 d.o.f. arm kit was assembled by students and used to understand simple robotic concepts like degree of freedom, gripper action, pick and place, palletisation and other topics in a lab syllabus together with online simulators where factory robots are simulated. Basic algorithms are explored by testing with the 5 dof puma arm. The addition of tactile and visual interfaces for pick and sort are discussed. Sample outputs are illustrated. (C) 2017 Elsevier Ltd. All rights reserved.
In this paper, we bring forward a BP algorithm condition modeling and an attitude modeling based on puma robot vacuum path planning. Considering the limitation of the traditional particle swarm optimization(PSO) in se...
详细信息
ISBN:
(纸本)9781479984640
In this paper, we bring forward a BP algorithm condition modeling and an attitude modeling based on puma robot vacuum path planning. Considering the limitation of the traditional particle swarm optimization(PSO) in searching space and easily running into local optimal points. We introduced the re-initialization mechanism based on the global information feedback to modified particle swarm optimization (MPSO) algorithm in this paper. To combine the MPSO algorithm with BP network algorithm before applying it in Vacuum Path Planning of puma robot. Then the mixed BP-MPSO optimal algorithm can not only avoids the difficulty in solving the inverse motion equations, but also ensures that the optimal solution, which can obtains the global optimal aim instead of falling into local extremer. The results of simulation experiment show that this algorithm can well enhance the efficiency of vacuum path planning.
In recent decades, Artificial Neural Networks (ANNs) have become the focus of considerable attention in many disciplines, including robot control. where they can be used to solve nonlinear control problems. One of the...
详细信息
In recent decades, Artificial Neural Networks (ANNs) have become the focus of considerable attention in many disciplines, including robot control. where they can be used to solve nonlinear control problems. One of these ANNs applications is that of the inverse kinematic problem, which is important in robot path planning. In this paper, a neural network is employed to analyse of inverse kinematics of puma 560 type robot. The neural network is designed to find exact kinematics of the robot. The neural network is a feedforward neural network (FNN). The FNN is trained with different types of learning algorithm for designing exact inverse model of the robot. The Unimation puma 560 is a robot with six degrees of freedom and rotational joints. Inverse neural network model of the robot is trained with different learning algorithms for finding exact model of the robot. From the simulation results, the proposed neural network has superior performance for modelling complex robot's kinematics.
Considering the deficiency of present robotic force control algorithm, we introduce artificial intelligent method in this paper. We attempt to combine fuzzy control theory with impedance control strategy, and attempt ...
详细信息
ISBN:
(纸本)0780386299
Considering the deficiency of present robotic force control algorithm, we introduce artificial intelligent method in this paper. We attempt to combine fuzzy control theory with impedance control strategy, and attempt to control the external force on the robotic end-effector by this quomodo. The structure of the system is presented and the force controller is designed. Finally we show the results based on the practical experiments. It is a more effective strategy to solve the robotic force control problem.
Planning appropriate trajectories can significantly increase the productivity of robot systems. To plan realistic time-optimal trajectories, the robot dynamics have to be described precisely. In this paper, a neural n...
详细信息
Planning appropriate trajectories can significantly increase the productivity of robot systems. To plan realistic time-optimal trajectories, the robot dynamics have to be described precisely. In this paper, a neural network based algorithm for time-optimal trajectory planning is introduced. This method utilises neural networks for representing the inverse dynamics of the robot. As the proposed neural networks,can be trained with data obtained from exciting the robot with given torque inputs, they will capture the complete dynamics of the robot system. Therefore, the trajectories generated will be more realistic than those obtained by using nominal dynamic equations based on nominal parameters. Time-optimal trajectories are generated for a puma robot to demonstrate the proposed method.
In this paper a control strategy for a redundant puma robot is presented. This robot is obtained from the conventional puma robot by addition of a joint parallel to the elbow joint. For redundancy resolution the follo...
详细信息
In this paper a control strategy for a redundant puma robot is presented. This robot is obtained from the conventional puma robot by addition of a joint parallel to the elbow joint. For redundancy resolution the following approach is chosen. From the position and pointing direction of the end effector of the puma robot the position and orientation of the fourth link of a 4R-manipulator is calculated and the redundancy is resolved for this manipulator. This is done by adding an equation to the relationship between the joint angles and position and orientation of the fourth link. By this approach a control strategy is derived that allows motions of the end effector of the puma robot in a large part of its work space and shows repeatable behaviour. Furthermore, the redundancy is utilized so that the flexture of the wrist is kept small.
In this paper, the identification problem of the puma 762 robot for grinding applications is considered by using several different recursive identification methods. A detailed procedure of modelling the robot is descr...
详细信息
In this paper, the identification problem of the puma 762 robot for grinding applications is considered by using several different recursive identification methods. A detailed procedure of modelling the robot is described. Various experiments have been performed using the puma 762/VAL II industrial robot equipped with a 4 Hp pneumatic grinder and a JR 3 force sensor. The puma 762 robot has been successfully modelled by a linear third order model with reliable accuracy. The nonlinearities of the robot have been investigated by utilizing different pseudorandom binary sequence (PRBS) signals. Clearly, these linear models, representing the input-output dynamics of the robot, will make it possible to design and develop adaptive controllers for the robotic grinding process.
暂无评论