Doctoral Dissertations

Date of Award

5-1999

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Mechanical Engineering

Major Professor

W. R. Hamel

Committee Members

R. Dubey, M. Abidi, R. Kress

Abstract

Hazardous environments encountered in nuclear clean-up tasks mandate the use of complex robotic systems in many situations. The operation of these systems is now performed primarily under teleoperation. This is, at best, five times slower than equivalent direct human contact operations.One way to increase remote work efficiency is to use automation for specific tasks. However, the unstructured, complex nature of the environment along with the inherent structural flexibility of mobile robot work systems makes task automation difficult and in meiny cases impossible.This research considers a quasi-static macroscopic modeling methodology that could be combined with sensor-guided manipulation schemes to achieve the needed operational accuracies for remote work task automation. Application of this methodology begins with an off-line analysis phase in which the system is identified in terms of the ideal D-H parameters and its structural elements. Themanipulator is modeled with fundamental components (i.e. beam elements, hydraulic elements, etc)and then analyzed to determine load dependent functions that predict deflections at each joint and the end of each link. Next, forces applied at the end-effector and gravity loads are projected into local link coordinates using the undeflected pose of the manipulator. These local loads are then used to calculate deflections which are expressed as 4 by 4 homogeneous transformations and inserted into the original manipulator transformations to predict end-effector position and orientation (anderror/deflection vector). The error/deflection vector is then used to determine corrective actions based on the manipulator flexibilities, pose and loading. This corrective action alters the manipulator commands such that the manipulator end-effector is moved to the desired location based on the error between the model predictions and commanded position using the ideal kinematics.The modeling methodology can readily be applied to any kinematic chain. This allows analysis of a conceptual system in terms of basic mechanics and structural deflections. The methodology allows components such as actuators or links to be interchanged in simulation so that alternative designs may be tested. This capability could help avoid potentially costly conceptual design flaws at a very early stage in the design process.Real-time compensation strategies have been developed so as to lessen concerns with structural deformation during use. The compensation strategies presented here show that the modeling methods can be used to increase the end-effector accuracy by calculating the deflections and command adjustments iteratively in real-time. The iterations show rapid convergence of the adjusted command positions to reach the desired end-effector location. The compensation methods discussed are easily altered to fit systems of any complexity, only requiring changes in the number of variables and the number of equations to solve. Most importantly, however, is that the modeling methodology,in conjunction with the compensation methods, can be used to correct for a significant fraction of the errors associated with manipulator flexibility effects. Implementation in a real-time system only involves changes in path planning, not in low-level control.The modeling methods and deflection predictions were verified using a sub-system of the OakRidge National Laboratory's Dual Arm Work Platform. The experimental method used simple,non-contact measurement devices that are minimally intrusive to the manipulator's workspace. The Results show good correlation between model and experimental results for some configurations. Experimental results can be extrapolated to predict that errors could be reduced from several inches to several tenths of an inch for systems like the Dual Arm Work Platform in some configurations.Continuing work will investigate applications to selective automation for Decontamination and Dismantlement tasks, using this work as a necessary foundation.

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