Title
Neural network control of a pneumatic robot arm
Abstract
Abstract A neural map algorithm has been employed to control a five-joint pneu- matic robot arm and gripper through feedback from two video cameras. The pneumatically driven robot arm,(SoftArm) employed,in this inves- tigation shares essential mechanical characteristics with skeletal muscle systems. To control the position of the arm, 200 neurons formed a net- work representing the three-dimensional workspace embedded,in a four- dimensional system of coordinates from the two cameras, and learned a three-dimensional set of pressures corresponding to the end eector,posi- tions, as well as a set of 3◊4 Jacobian matrices for interpolating between these positions. The gripper orientation was achieved through adaptation of a 1 ◊ 4 Jacobian matrix for a fourth joint. Because of the properties of the rubber-tube actuators of the SoftArm, the position as a function of supplied pressure is nonlinear, nonseparable, and exhibits hysteresis. Nevertheless, through the neural network learning algorithm the position could be controlled to an accuracy of about one pixel ( 3 mm) after two hundred,learning steps and the orientation could be controlled to two pixels after eight hundred learning steps. This was achieved through employment,of a linear correction algorithm using the Jacobian matrices mentioned above. Applications of repeated corrections in each position-
Year
DOI
Venue
1994
10.1109/21.259683
IEEE Transactions on Systems, Man, and Cybernetics
Keywords
DocType
Volume
feedback,learning (artificial intelligence),manipulators,neural nets,position control,1×4 Jacobian matrix,3×4 Jacobian matrices,SoftArm,biological visuo-motor control,five-joint pneumatic robot arm,four-dimensional system,gripper,learning algorithm,linear correction algorithm,neural map algorithm,neural network control,pneumatic robot arm,robust control algorithm,three-dimensional workspace
Journal
24
Issue
ISSN
Citations 
1
0018-9472
26
PageRank 
References 
Authors
7.54
6
4
Name
Order
Citations
PageRank
Ted Hesselroth1328.48
Kakali Sarkar218418.03
P. Patrick Van Der Smagt327435.19
Klaus Schulten42161467.19