Author
Simons, Anya L.
Other Contributors
Derby, Stephen J.;
Date Issued
1992-12
Subject
Engineering science
Degree
MS;
Terms of Use
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute (RPI), Troy, NY. Copyright of original work retained by author.;
Abstract
Popular and novel neural network architecture and training approaches are combined with conventional trajectory smoothing and obstacle avoidance techniques to demonstrate the feasibility of an industrial robot that can safely, reliably, and effectively interact with humans, avoid unforeseen moving obstacles in a stable fashion, and maintain integrity of its payload. An appreciation is sought for the level of hardware and process integration required for the implementation of a successful comprehensive automated manufacturing package. Extensions of the methods demonstrated are discussed.;
Description
School of Engineering; December 1992
Department
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Access
Restricted to current Rensselaer faculty, staff and students in accordance with the Rensselaer Standard license. Access inquiries may be directed to the Rensselaer Libraries.;
