Optimum Robot Design Based on Task Specifications Using Evolutionary Techniques and Kinematic, Dynamic, and Structural Constraints

Shiakolas, Panos S.; Koladiya, D.; Kebrle, J.

doi:10.1115/imece2002-32477

Cited by 9 publications

(14 citation statements)

References 19 publications

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“…Shiakolas et al 9 applied three evolutionary techniques to optimize the required torque of robots for a defined motion subject to different constraints. However, application of evolutionary techniques to determine optimal parameters of manipulator for minimum performance variations is rare.…”

Section: Background Of Researchmentioning

confidence: 99%

Optimal design of manipulator parameter using evolutionary optimization techniques

Rout

Mittal

2009

Robotica

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SUMMARYA 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.

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Section: Background Of Researchmentioning

confidence: 99%

Optimal design of manipulator parameter using evolutionary optimization techniques

Rout

Mittal

2009

Robotica

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“…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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“…[56] and elitism was excercised in refs. [35,38,41,46,51,52,64,81,90]. Truncation strategy appeared in ref.…”

Section: Survivor Selectionmentioning

confidence: 99%

“…[50,56,63,66,74,83,84] and they were amended with elitism, or other selection methods. 35,38,43,45,46,48,51,68,87,88 A GA with novelty search and an objective-based GA found application in ref. [70] where individuals that performed differently were rewarded if they possessed novelty.…”

Section: Different Eas Appliedmentioning

confidence: 99%

A survey on evolutionary-aided design in robotics

Prabhu¹,

Seals²,

Kyberd³

et al. 2018

Robotica

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SUMMARYThe evolutionary-aided design process is a method to find solutions to design and optimisation problems. Evolutionary algorithms (EAs) are applied to search for optimal solutions from a solution space that evolves over several generations. EAs have found applications in many areas of robotics. This paper covers the efforts to determine body morphology of robots through evolution and body morphology with the controller of robots or similar creatures through co-evolution. The works are reviewed from the perspective of how different algorithms are applied and includes a brief explanation of how they are implemented.

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Optimum Robot Design Based on Task Specifications Using Evolutionary Techniques and Kinematic, Dynamic, and Structural Constraints

Cited by 9 publications

References 19 publications

Optimal design of manipulator parameter using evolutionary optimization techniques

Optimal design of manipulator parameter using evolutionary optimization techniques

Goal Directed Synthesis of Serial Manipulators Based on Task Descriptions

A survey on evolutionary-aided design in robotics

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