Engineering topics

Saridis, George N.

Publications and source records attributed to Saridis, George N..

13 records

NASA NTRS1992

Petri net controllers for distributed robotic systems

Petri nets are a well established modelling technique for analyzing parallel systems. When coupled with an event-driven operating system, Petri nets can provide an effective means for integrating and controlling the functions of distributed robotic applications. Recent work has shown that Petri net graphs can also serve as remarkably intuitive operator interfaces. In this paper, the advantages of using Petri nets as high-level controllers to coordinate robotic functions are outlined, the considerations for designing Petri net controllers are discussed, and simple Petri net structures for implementing an interface for operator supervision are presented. A detailed example is presented which illustrates these concepts for a sensor-based assembly application.

Lefebvre, D. R.↗

NASA NTRS1991

Simulation of cooperating robot manipulators on a mobile platform

The dynamic equations of motion are presented for two or more cooperating manipulators on a freely moving mobile platform. The system of cooperating robot manipulators forms a closed kinematic chain where the force of interaction must be included in the formulation of robot and platform dynamics. The formulation includes the full dynamic interactions from arms to platform and arm tip to arm tip, and the possible translation and rotation of the platform. The equations of motion are shown to be identical in structure to the fixed-platform cooperative manipulator dynamics. The number of DOFs of the system is sufficiently large to make recursive dynamic calculation methods potentially more efficient than closed-form solutions. A complete simulation with two 6-DOF manipulators of a free-floating platform is presented along a with a multiple-arm controller to position the common load.

Murphy, Stephen H.↗

NASA NTRS1991

Architectures for intelligent machines

The theory of intelligent machines has been recently reformulated to incorporate new architectures that are using neural and Petri nets. The analytic functions of an intelligent machine are implemented by intelligent controls, using entropy as a measure. The resulting hierarchical control structure is based on the principle of increasing precision with decreasing intelligence. Each of the three levels of the intelligent control is using different architectures, in order to satisfy the requirements of the principle: the organization level is moduled after a Boltzmann machine for abstract reasoning, task planning and decision making; the coordination level is composed of a number of Petri net transducers supervised, for command exchange, by a dispatcher, which also serves as an interface to the organization level; the execution level, include the sensory, planning for navigation and control hardware which interacts one-to-one with the appropriate coordinators, while a VME bus provides a channel for database exchange among the several devices. This system is currently implemented on a robotic transporter, designed for space construction at the CIRSSE laboratories at the Rensselaer Polytechnic Institute. The progress of its development is reported.

Saridis, George N.↗

NASA NTRS1991

Reliable automatic plan selection for visual robotic positioning

Reliability analysis techniques developed for robotics are applied to a six-DOF (degree-of-freedom) visual positioning system. The task is to measure an object's pose and then grip the object reliably subject to time and accuracy constraints. Errors due to pixel truncation in the stadimetric vision system, forward kinematic and inverse kinematic uncertainties, and joint position and velocity noise are stochastically modeled. Simulation results for PUMA 500 kinematic and dynamic characteristics are presented.

Mcinroy, John E.↗

NASA NTRS1990

Acceleration and torque feedback for robotic control - Experimental results

Gross motion control of robotic manipulators typically requires significant on-line computations to compensate for nonlinear dynamics due to gravity, Coriolis, centripetal, and friction nonlinearities. One controller proposed by Luo and Saridis avoids these computations by feeding back joint acceleration and torque. This study implements the controller on a Puma 600 robotic manipulator. Joint acceleration measurement is obtained by measuring linear accelerations of each joint, and deriving a computationally efficient transformation from the linear measurements to the angular accelerations. Torque feedback is obtained by using the previous torque sent to the joints. The implementation has stability problems on the Puma 600 due to the extremely high gains inherent in the feedback structure. Since these high gains excite frequency modes in the Puma 600, the algorithm is modified to decrease the gain inherent in the feedback structure. The resulting compensator is stable and insensitive to high frequency unmodeled dynamics. Moreover, a second compensator is proposed which uses acceleration and torque feedback, but still allows nonlinear terms to be fed forward. Thus, by feeding the increment in the easily calculated gravity terms forward, improved responses are obtained. Both proposed compensators are implemented, and the real time results are compared to those obtained with the computed torque algorithm.

Mclnroy, John E.↗

NASA NTRS1990

A Boltzmann machine for the organization of intelligent machines

A three-tier structure consisting of organization, coordination, and execution levels forms the architecture of an intelligent machine using the principle of increasing precision with decreasing intelligence from a hierarchically intelligent control. This system has been formulated as a probabilistic model, where uncertainty and imprecision can be expressed in terms of entropies. The optimal strategy for decision planning and task execution can be found by minimizing the total entropy in the system. The focus is on the design of the organization level as a Boltzmann machine. Since this level is responsible for planning the actions of the machine, the Boltzmann machine is reformulated to use entropy as the cost function to be minimized. Simulated annealing, expanding subinterval random search, and the genetic algorithm are presented as search techniques to efficiently find the desired action sequence and illustrated with numerical examples.

Moed, Michael C.↗

NASA NTRS1990

A coordination theory for intelligent machines

A formal model for the coordination level of intelligent machines is established. The framework of the coordination level investigated consists of one dispatcher and a number of coordinators. The model called coordination structure has been used to describe analytically the information structure and information flow for the coordination activities in the coordination level. Specifically, the coordination structure offers a formalism to (1) describe the task translation of the dispatcher and coordinators; (2) represent the individual process within the dispatcher and coordinators; (3) specify the cooperation and connection among the dispatcher and coordinators; (4) perform the process analysis and evaluation; and (5) provide a control and communication mechanism for the real-time monitor or simulation of the coordination process. A simple procedure for the task scheduling in the coordination structure is presented. The task translation is achieved by a stochastic learning algorithm. The learning process is measured with entropy and its convergence is guaranteed. Finally, a case study of the coordination structure with three coordinators and one dispatcher for a simple intelligent manipulator system illustrates the proposed model and the simulation of the task processes performed on the model verifies the soundness of the theory.

Wang, Fei-Yue↗

NASA NTRS1990

Reliability analysis in intelligent machines

Given an explicit task to be executed, an intelligent machine must be able to find the probability of success, or reliability, of alternative control and sensing strategies. By using concepts for information theory and reliability theory, new techniques for finding the reliability corresponding to alternative subsets of control and sensing strategies are proposed such that a desired set of specifications can be satisfied. The analysis is straightforward, provided that a set of Gaussian random state variables is available. An example problem illustrates the technique, and general reliability results are presented for visual servoing with a computed torque-control algorithm. Moreover, the example illustrates the principle of increasing precision with decreasing intelligence at the execution level of an intelligent machine.

Mcinroy, John E.↗

NASA NTRS1990

Recursive calculation of geared robot manipulator dynamics

A recursive formulation is presented for the calculation of the inverse and forward dynamics of rigid robot manipulators with gear systems on each joint. The complete effects of the gear ratios and the gyroscopic effects of the spinning motor/gear are included in the recursive formulation. The forward dynamics solution recursively calculates the joint accelerations when given motor torques, and the number of computations grows linearly with the number of links.

Murphy, Steve H.↗

NASA NTRS1990

Simulation of cooperating robot manipulators on a mobile platform

The dynamic equations of motion for two manipulators holding a common object on a freely moving mobile platform are developed. The full dynamic interactions from arms to platform and arm-tip to arm-tip are included in the formulation. The development of the closed chain dynamics allows for the use of any solution for the open topological tree of base and manipulator links. In particular, because the system has 18 degrees of freedom, recursive solutions for the dynamic simulation become more promising for efficient calculations of the motion. Simulation of the system is accomplished through a MATLAB program, and the response is visualized graphically using the SILMA Cimstation.

Murphy, Steve H.↗

NASA NTRS1990

Momentum limiting velocity controls for robotic manipulators

Robotic tasks in space require manipulating massive objects capable of attaining large momentum. The momentum can pose hazardous conditions and introduce destabilizing effects on a space platform. Consequently, a technique for limiting the momentum applied to objects under manipulation subject to arbitrary velocity input commands is proposed. The algorithm does not require mass position or inertia information about the object, and it takes actuator limitations into account in forming the momentum limits. To evaluate the probability that a velocity trajectory will fall within the momentum bounds, reliability theory is employed. This enables autonomously generated trajectories to be validated for compliance with momentum limits.

Mcinroy, John E.↗

NASA NTRS1989

A Boltzmann machine for the organization of intelligent machines

In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved to converge to the minimum of a cost function. Finally, simulations will show the effectiveness of a variety of search techniques for the intelligent machine.

Moed, Michael C.↗

NASA NTRS1987

Analytical design of intelligent machines

The problem of designing 'intelligent machines' to operate in uncertain environments with minimum supervision or interaction with a human operator is examined. The structure of an 'intelligent machine' is defined to be the structure of a Hierarchically Intelligent Control System, composed of three levels hierarchically ordered according to the principle of 'increasing precision with decreasing intelligence', namely: the organizational level, performing general information processing tasks in association with a long-term memory; the coordination level, dealing with specific information processing tasks with a short-term memory; and the control level, which performs the execution of various tasks through hardware using feedback control methods. The behavior of such a machine may be managed by controls with special considerations and its 'intelligence' is directly related to the derivation of a compatible measure that associates the intelligence of the higher levels with the concept of entropy, which is a sufficient analytic measure that unifies the treatment of all the levels of an 'intelligent machine' as the mathematical problem of finding the right sequence of internal decisions and controls for a system structured in the order of intelligence and inverse order of precision such that it minimizes its total entropy. A case study on the automatic maintenance of a nuclear plant illustrates the proposed approach.

Saridis, George N.↗