Title

Massively parallel GPU computing of continuum robotic dynamics

Advisor

Jones, Bryan

Committee Member

Dampier, David

Committee Member

Abdelwahed, Sherif

Date of Degree

5-1-2011

Original embargo terms

MSU Only Indefinitely

Document Type

Graduate Thesis - Open Access

Major

Computer Engineering

Degree Name

Master of Science

College

James Worth Bagley College of Engineering

Department

Department of Electrical and Computer Engineering

Abstract

Continuum robots, with the capability of bending and extending at any point along their length mimic the abilities of an octopus arm or an elephant trunk. These manipulators present a number of exciting possibilities. While calculating a static solution for the system has been proven with certain models to produce satisfactory results [1], this approach ignores the significant effects a dynamics solution captures. However, adding time and studying the physical effects produced on a continuum robot involves calculation of the robot’s shape at a number of discrete points. Typically, the separation between points will be very small and thus a solution requires large amounts of computational power. We present a method to improve calculation speed for dynamic problems with the use of CUDA, a framework for parallel GPU computing. GPUs are ideally suited for massively parallel computations because of their multi-processor architecture. Our dynamics solution will take advantage of this parallel environment.

URI

https://hdl.handle.net/11668/16292

Comments

dynamics||continuum||robotics||gpu||cuda||neural networks

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