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  5. Application of an inexpensive ultrasonic sensor as an object detection device for a robotic arm
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Application of an inexpensive ultrasonic sensor as an object detection device for a robotic arm

Date Issued
December 1, 1990
Author(s)
Asghar, Qamar
Advisor(s)
James A. Euler
Additional Advisor(s)
R. V. Dubey
S. T. Becker
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/34028
Abstract

Kinematically redundant robots have been the subject of many investigations in which researchers have tried to avoid obstacles by using the available degree of redundancy. These schemes are usually based on the assumption of a well defined obstacle location and position in the robot's work space. A more complete solution to this problem includes a continuous feedback mechanism for accurate location of moving obstacles or objects in the robot's work envelope. A robot which can "see", can prove to be more dextrous in the performance of complex tasks while at the same time it requires less stringent control mechanisms than preprogrammed machines. A sensory, trainable system is also adaptable to a much larger variety of tasks, thus achieving a degree of universality that ultimately translates into lower production and maintenence cost. An obstacle avoidance scheme based on sensory feedback is presented for the kinematic control of a robotic manipulator with a single degree of redundancy, which can be extended to manipulators with multiple degrees of redundancy. An inexpensive ultrasonic sensor is used to locate obstacles in the robot's workspace and provide feedback for modification of the robot's wrist trajectory. The kinematic control scheme which uses the feedback from the sensor for local optimization of trajectory parameter is based upon the gradient projection method developed by Dubey and Euler et al. [5]. This study also explores the possibilities of using the sensor as an inexpensive feedback control loop device to duplicate the results of computer vision.

Degree
Master of Science
Major
Mechanical Engineering
File(s)
Thumbnail Image
Name

Thesis90A834.pdf

Size

3.96 MB

Format

Unknown

Checksum (MD5)

7150c9b0ac45a4de06f32aa4e6cbb058

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