Optimum module selection and design based on kinematic and dynamic task requirements using DADS and genetic algorithms

Panayiotis S. Shiakolas; Syed Faisal Haider

doi:10.1117/12.360349

26 August 1999 Optimum module selection and design based on kinematic and dynamic task requirements using DADS and genetic algorithms

Panayiotis S. Shiakolas, Syed Faisal Haider

Author Affiliations +

Proceedings Volume 3839, Sensor Fusion and Decentralized Control in Robotic Systems II; (1999) https://doi.org/10.1117/12.360349
Event: Photonics East '99, 1999, Boston, MA, United States

Abstract

A novel approach is presented to design an optimized robot manipulator based on the task description taking into account the workspace and the dynamic properties inherent in the system by selecting components from a library of available components. This approach requires representing a robot configuration using Denavit-Hartenberg parameters and defining the desired trajectory. A dynamic analysis package (DADS) is used to create and analyze the model automatically via a in-house developed code, which eliminates the user interaction with DADS enabling us to model any serial link manipulator instantly. The results of the analysis are used by another program to evalute a fitness value. This fitness value is then passed to the genetic algorithm, which is used as the optimization tool. Then, an iteration is established until defined convergence criteria are met. The approach has been applied in the selection of geometric characteristics for the links of different configuration robotic manipulators with the objective being to minimize the required torque based on the defined task.

Citation Download Citation

Panayiotis S. Shiakolas and Syed Faisal Haider "Optimum module selection and design based on kinematic and dynamic task requirements using DADS and genetic algorithms", Proc. SPIE 3839, Sensor Fusion and Decentralized Control in Robotic Systems II, (26 August 1999); https://doi.org/10.1117/12.360349

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