Showing papers on "Autonomous system (mathematics) published in 1989"

A Control Architecture for an Advanced Fault-Tolerant Robot System

Abstract: A major issue in robotic research is the development of advanced autonomous robots which are able to solve a difficult task in a complex environment. Besides the need for powerful sensing and planning capabilities, an autonomous system must incorporate a highly sophisticated control architecture. This paper describes an advanced robot control system which is being developed at the Institute for Real-Time Computer Control Systems and Robotics of the University of Karlsrube. As a test environment for the implementation of this architecture, the autonomous moible two-arm robot system KAMRO is used.

Fuzzy rule-based motion controller for an autonomous mobile robot

Abstract: Intelligent control of mobile systems allows for hierarchical structures that utilize sensory data with various levels of accuracy. This paper discusses a rule-based approach for the control problem. The assumed inexactness in world description is represented by fuzzy memberships, and the state space is discretized into a linguistic vocabulary. Fuzzy motion control rules that have been experimentally derived, are then used in a fuzzy inference mechanism to give the final control command to robot actuators. Finally, the developed algorithm is tested for real-time control applications.

Steady-State Solutions and Limit Sets

Abstract: In this section, we define dynamical systems and present some useful facts from the theory of differential equations.

Autonomous Knowledge-Based Navigation in an Unknown Two-Dimensional Environment with Convex Polygon Obstacles

Abstract: Navigation of autonomous vehicles in environments where the exact locations of obstacles are initially know has been the focus of research for two decades. More recently, algorithms for controlling progress through unknown environments have been proposed. The utilization of knowledge-based systems for studying the behavior of an autonomous vehicles presents new challenges for research. A knowledge-driven autonomous system simulation was developed which enabled an autonomous mobile system to move in a two-dimensional, obstacle strewn, environment and to use a simulated ranging/vision sensor to test whether a selected goal position was visible or whether the goal was obscured by one or more of the polygon obstacles. As the mobile system gained information about the location of obstacles, that knowledge is added to the system's knowledge-base. High-level navigation rules were fired when necessary conditions in the knowledge base existed. The necessary low-level computations (eg., vertex visibilities, etc) were, when required within the context of a selected rule, carried or' through appropriate Lisp functions. The knowledge-based program was implemented in the generalized decision-making paradigm, OPS5.

Navigation and learning experiments by an autonomous robot

Abstract: Developing an autonomous mobile robot capable of navigation, surveillance and manipulation in complex and dynamic environments is a key research activity at CESAR, Oak Ridge National Laboratory's Center for Engineering Systems Advanced Research. The latest series of completed experiments was performed using the autonomous mobile robot HERMIES-IIB ( H ostile E nvironment R obotic I ntelligence E xperiment Series II-B).

Autonomous Knowledge-Based Navigation In An Unkown Two-Dimensional Environment With Convex Polygon Obstacles

Abstract: Navigation of autonomous vehicles in environments where the exact locations of obstacles are know has been the focus of research for two decades. More recently, algorithms for controlling progress through unknown environments have been proposed. The utilization of knowledge-based systems for studying the behavior of an autonomous vehicles has not received much study. A knowledge-driven autonomous system simulation was developed which enabled an autonomous mobile system to move in a two-dimensional environment and to use a simulated ranging/vision sensor to test whether a selected goal position was visible or whether the goal was obscured by one of the multiple polygon obstacles. As the mobile system gains information about the location of obstacles, it is added to the system's knowledge-base. Considerable attention was given to the computation of what vertices were mutually visible in the multi-obstacle environment and that computation was carried out in Lisp. The study relied on a program implemented in a generalized decision-making paradigm, OPS5.