Optimal design of manipulator parameter using evolutionary optimization techniques

Authors:
B. k. Rout;R. k. Mittal
Affiliations:
Mechanical engineering group, birla institute of technology and science, pilani – 333031, rajasthan, india;Mechanical engineering group, birla institute of technology and science, pilani – 333031, rajasthan, india
Venue:
Robotica
Year:
2010

Citing 10
Cited 1

Robot Dynamics and Control

Robot Dynamics and Control
Introduction to Robotics: Mechanics and Control

Introduction to Robotics: Mechanics and Control
Time Series Analysis: Forecasting and Control

Time Series Analysis: Forecasting and Control
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces

Journal of Global Optimization
An agent-based approach to the design of rapidly deployable fault-tolerant manipulators

An agent-based approach to the design of rapidly deployable fault-tolerant manipulators
Fast constrained global minimax optimization of robot parameters

Robotica
Using a new GA-based multiobjective optimization technique for the design of robot arms

Robotica
Optimal placement of a two-link planar manipulator using a genetic algorithm

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Application of genetic programming to the calibration of industrial robots

Computers in Industry
Screening of factors influencing the performance of manipulator using combined array design of experiment approach

Robotics and Computer-Integrated Manufacturing

Integrated dimensional and drive-train design optimization of a light-weight anthropomorphic arm

Robotics and Autonomous Systems

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Abstract

A robot must have high positioning accuracy and repeatability for precise applications. However, variations in performance are observed due to the effect of uncertainty in design and process parameters. So far, there has been no attempt to optimize the design parameters of manipulator by which performance variations will be minimum. A modification in differential evolution optimization technique is proposed to incorporate the effect of noises in the optimization process and obtain the optimal design of manipulator, which is insensitive to noises. This approach has been illustrated by selecting optimal parameter of 2-DOF RR planar manipulator and 4-DOF SCARA manipulator. The performance of proposed approach has been compared with genetic algorithm with similar modifications. It is observed that the optimal results are obtained with lesser computations in case of differential evolution technique. This approach is a viable alternative for costly prototype testing, where only kinematic and dynamic models of manipulator are dealt with.