Kinematics of the MIT-AI-VICARM Manipulator

This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-70-A-0362-0005.This paper describes the basic geometry of the electric manipulator designed for the Artificial Intelligence Laboratory by Victor Scheinman while on leave from Stanford University. The procedure for finding a set of joint angles that will place the terminal device in a desired position and orientation is developed in detail. This is on of the basic primitives that an arm controller should have. The orientation is specified in terms of Euler-angles. Typically eight sets of joint angles will produce the same terminal device position and orientation.MIT Artificial Intelligence Laborator

Artificial intelligence in control of real dynamic systems.

PhDA real dynamic plant is used to compare, test and assess the present theoretical techniques of adaptive, learning or intelligent control under practical criteria. Work of this nature has yet to be carried out if "intelligent control" is to have a place in everyday practice. The project follows a natural pattern of development, the construction of computer programmes being an important part of it. First, a. real plant - a model steam engine - and its electronic interface with a general purpose digital computer are designed and built as part of the project. A rough mathematical model of the plant is then obtained through identification tests. Second, conventional control of the plant is effected using digital techniques and the above mentioned mathematical model, and the results are saved to compare with and evaluate the results of "intelligent control". Third, a few well-known adaptive or learning control algorithms are investigated and implemented. These tests bring out certain practical problems not encountered or not given due consideration in theoretical or simulation studies. Alternatively, these problems materialise because assumptions made on paper are not readily available in practice. The most important of these problematic. assumptions are those relating to computational time and storage, convergence of the adaptive or learning algorithm and the training of the controller. The human operator as a distinct candidate for the trainer is also considered and the problems therein are discussed. Finally, the notion of fuzzy sets and logic is viewed from the control point and a controller using this approach is developed and implemented. The operational advantages and the results obtained, albeit preliminary, demonstrate the potential power of this notion and provide the grounds for further work in this area

Advanced Automation for Space Missions

The feasibility of using machine intelligence, including automation and robotics, in future space missions was studied