Article

Randomized Optimal Design of Parallel Manipulators

Hong Kong Univ. of Sci. & Technol. (HKUST), Hong Kong
IEEE Transactions on Automation Science and Engineering (impact factor: 1.46). 05/2008; DOI:10.1109/TASE.2007.909446 pp.223 - 233
Source: IEEE Xplore

ABSTRACT This work intends to deal with the optimal kinematic synthesis problem of parallel manipulators under a unified framework. Observing that regular (e.g., hyper-rectangular) workspaces are desirable for most machines, we propose the concept of effective regular workspace, which reflects simultaneously requirements on the workspace shape and quality. The effectiveness of a workspace is characterized by the dexterity of the mechanism over every point in the workspace. Other performance indices, such as manipulability and stiffness, provide alternatives of dexterity characterization of workspace effectiveness. An optimal design problem, including constraints on actuated/passive joint limits and link interference, is then formulated to find the manipulator geometry that maximizes the effective regular workspace. This problem is a constrained nonlinear optimization problem without explicitly analytical expression. Traditional gradient based approaches may have difficulty in searching the global optimum. The controlled random search technique, as reported robust and reliable, is used to obtain an numerical solution. The design procedure is demonstrated through examples of a Delta robot and a Gough-Stewart platform.

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Keywords

analytical expression
 
constrained nonlinear optimization problem
 
controlled random search technique
 
Delta robot
 
design procedure
 
effective regular workspace
 
global optimum
 
Gough-Stewart platform
 
manipulator geometry
 
numerical solution
 
optimal design problem
 
optimal kinematic synthesis problem
 
parallel manipulators
 
performance indices
 
regular
 
Traditional gradient
 
unified framework
 
workspace
 
workspace effectiveness
 
workspace shape
 

Yunjiang Lou