Task-oriented optimal configuration structure in a three-dimensional self-organizing robot by genetic algorithms

Izumi, Kiyotaka; Tamura, H.; Watanabe, Keigo

doi:10.1109/icsmc.1999.825354

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…Authors in [5,9,11] recommend the use of Genetic Algorithms (GA) for designing the structure of self-organizing and modular robotic systems. In [29], authors Shiakolas et al use evolutionary optimization approaches to optimize the design of a SCARA manipulator.…”

Section: Task-based Design Approachmentioning

confidence: 99%

Goal Directed Synthesis of Serial Manipulators Based on Task Descriptions

Patel

Sobh

Mahmood

2014

Chaos Modeling and Control Systems Design

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Computing the optimal geometric structure of manipulators is one of the most intricate problems in contemporary robot kinematics. Robotic manipulators are designed and built to perform certain predetermined tasks. There is a very close relationship between the structure of the manipulator and its kinematic performance. It is therefore important to incorporate such task requirements during the design and synthesis of the robotic manipulators. Such task requirements and performance constraints can be specified in terms of the required end-effector positions, orientations and velocities along the task trajectory. In this work, we present a comprehensive method to develop the optimal geometric structure (DH parameters) of a non-redundant six degree of freedom serial manipulator from task descriptions. This methodology is devised to investigate possible manipulator configurations that can satisfy the task performance requirements under imposed joint constraints. Out of all the possible structures, the structures that can reach all the task points with the required orientations selected. Next, these candidate structures are then tested to see if they can attain end-effector velocities in arbitrary directions within the user defined joint constraints, so that they can deliver the best kinematic performance. Finally, the synthesized structures are tested to see if they perform the task under the operating constraints. In this work, we also present a novel approach for computing the inverse kinematics using Particle Swarm Optimization (PSO).

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Section: Task-based Design Approachmentioning

confidence: 99%

Goal Directed Synthesis of Serial Manipulators Based on Task Descriptions

Patel

Sobh

Mahmood

2014

Chaos Modeling and Control Systems Design

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Task based synthesis of serial manipulators

Patel

Sobh

2015

Journal of Advanced Research

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Computing the optimal geometric structure of manipulators is one of the most intricate problems in contemporary robot kinematics. Robotic manipulators are designed and built to perform certain predetermined tasks. There is a very close relationship between the structure of the manipulator and its kinematic performance. It is therefore important to incorporate such task requirements during the design and synthesis of the robotic manipulators. Such task requirements and performance constraints can be specified in terms of the required end-effector positions, orientations and velocities along the task trajectory. In this work, we present a comprehensive method to develop the optimal geometric structure (DH parameters) of a non-redundant six degree of freedom serial manipulator from task descriptions. In this work we define, develop and test a methodology to design optimal manipulator configurations based on task descriptions. This methodology is devised to investigate all possible manipulator configurations that can satisfy the task performance requirements under imposed joint constraints. Out of all the possible structures, the structures that can reach all the task points with the required orientations are selected. Next, these candidate structures are tested to see whether they can attain end-effector velocities in arbitrary directions within the user defined joint constraints, so that they can deliver the best kinematic performance. Additionally least power consuming configurations are also identified.

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A survey of robotic control systems constructed by using evolutionary computations

Watanabe

Izumi

IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028)

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Task-oriented optimal configuration structure in a three-dimensional self-organizing robot by genetic algorithms

Cited by 3 publications

References 5 publications

Goal Directed Synthesis of Serial Manipulators Based on Task Descriptions

Goal Directed Synthesis of Serial Manipulators Based on Task Descriptions

Task based synthesis of serial manipulators

A survey of robotic control systems constructed by using evolutionary computations

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