Book•
A robust layered control system for a mobile robot
01 Jun 1991-pp 2-27
TL;DR: A new architecture for controlling mobile robots is described, building a robust and flexible robot control system that has been used to control a mobile robot wandering around unconstrained laboratory areas and computer machine rooms.
Abstract: A new architecture for controlling mobile robots is described. Layers of control system are built to let the robot operate at increasing levels of competence. Layers are made up of asynchronous modules that communicate over low-bandwidth channels. Each module is an instance of a fairly simple computational machine. Higher-level layers can subsume the roles of lower levels by suppressing their outputs. However, lower levels continue to function as higher levels are added. The result is a robust and flexible robot control system. The system has been used to control a mobile robot wandering around unconstrained laboratory areas and computer machine rooms. Eventually it is intended to control a robot that wanders the office areas of our laboratory, building maps of its surroundings using an onboard arm to perform simple tasks.
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01 Jan 1992TL;DR: This book discusses the evolution of architecture, primitive functions, terminals, sufficiency, and closure, and the role of representation and the lens effect in genetic programming.
Abstract: Background on genetic algorithms, LISP, and genetic programming hierarchical problem-solving introduction to automatically-defined functions - the two-boxes problem problems that straddle the breakeven point for computational effort Boolean parity functions determining the architecture of the program the lawnmower problem the bumblebee problem the increasing benefits of ADFs as problems are scaled up finding an impulse response function artificial ant on the San Mateo trail obstacle-avoiding robot the minesweeper problem automatic discovery of detectors for letter recognition flushes and four-of-a-kinds in a pinochle deck introduction to biochemistry and molecular biology prediction of transmembrane domains in proteins prediction of omega loops in proteins lookahead version of the transmembrane problem evolutionary selection of the architecture of the program evolution of primitives and sufficiency evolutionary selection of terminals evolution of closure simultaneous evolution of architecture, primitive functions, terminals, sufficiency, and closure the role of representation and the lens effect Appendices: list of special symbols list of special functions list of type fonts default parameters computer implementation annotated bibliography of genetic programming electronic mailing list and public repository
13,487 citations
Book•
01 Jan 1999
TL;DR: The Cognitive Science of Philosophy: A Cognitive Science Of Basic Philosophical Ideas as mentioned in this paper The Cognitive science of philosophy is a branch of the philosophy of early Greek metaphysics and philosophy of philosophy.
Abstract: * Introduction: Who Are We? How The Embodied Mind Challenges The Western Philosophical Tradition * The Cognitive Unconscious * The Embodied Mind * Primary Metaphor and Subjective Experience * The Anatomy of Complex Metaphor * Embodied Realism: Cognitive Science Versus A Priori Philosophy * Realism and Truth * Metaphor and Truth The Cognitive Science Of Basic Philosophical Ideas * The Cognitive Science of Philosophical Ideas * Time * Events and Causes * The Mind * The Self * Morality The Cognitive Science Of Philosophy * The Cognitive Science of Philosophy * The Pre-Socratics: The Cognitive Science of Early Greek Metaphysics * Plato * Aristotle * Descartes and the Enlightenment Mind * Kantian Morality * Analytic Philosophy * Chomskys Philosophy and Cognitive Linguistics * The Theory of Rational Action * How Philosophical Theories Work Embodied Philosophy * Philosophy in the Flesh
6,747 citations
TL;DR: Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents as discussed by the authors ; agent architectures can be thought of as software engineering models of agents; and agent languages are software systems for programming and experimenting with agents.
Abstract: The concept of an agent has become important in both Artificial Intelligence (AI) and mainstream computer science. Our aim in this paper is to point the reader at what we perceive to be the most important theoretical and practical issues associated with the design and construction of intelligent agents. For convenience, we divide these issues into three areas (though as the reader will see, the divisions are at times somewhat arbitrary). Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents. Agent architectures can be thought of as software engineering models of agents;researchers in this area are primarily concerned with the problem of designing software or hardware systems that will satisfy the properties specified by agent theorists. Finally, agent languages are software systems for programming and experimenting with agents; these languages may embody principles proposed by theorists. The paper is not intended to serve as a tutorial introduction to all the issues mentioned; we hope instead simply to identify the most important issues, and point to work that elaborates on them. The article includes a short review of current and potential applications of agent technology.
6,714 citations
01 Jan 1988
TL;DR: Brooks et al. as mentioned in this paper decompose an intelligent system into independent and parallel activity producers which all interface directly to the world through perception and action, rather than interface to each other particularly much.
Abstract: Brooks, R.A., Intelligence without representation, Artificial Intelligence 47 (1991) 139159. Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporateeverything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments.
4,202 citations
TL;DR: Brooks et al. as discussed by the authors decompose an intelligent system into independent and parallel activity producers which all interface directly to the world through perception and action, rather than interface to each other particularly much.
3,783 citations
References
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6,484 citations
TL;DR: A version of the Marr-Poggio-Grimson algorithm that embodies modifications to the model, and its performance on a series of natural images is illustrated.
Abstract: Computational models of the human stereo system can provide insight into general information processing constraints that apply to any stereo system, either artificial or biological. In 1977 Marr and Poggio proposed one such computational model, which was characterized as matching certain feature points in difference-of-Gaussian filtered images and using the information obtained by matching coarser resolution representations to restrict the search space for matching finer resolution representations. An implementation of the algorithm and its testing on a range of images was reported in 1980. Since then a number of psychophysical experiments have suggested possible refinements to the model and modifications to the algorithm. As well, recent computational experiments applying the algorithm to a variety of natural images, especially aerial photographs, have led to a number of modifications. In this paper, we present a version of the Marr-Poggio-Grimson algorithm that embodies these modifications, and we illustrate its performance on a series of natural images.
601 citations
01 Mar 1985
TL;DR: A learning technique is described in which the robot develops a global model and a network of places, which is useful for navigation in a finite, pre-learned domain such as a house, office, or factory.
Abstract: A navigation system is described for a mobile robot equipped with a rotating ultrasonic range sensor. This navigation system is based on a dynamically maintained model of the local environment, called the composite local model. The composite local model integrates information from the rotating range sensor, the robot's touch sensor, and a pre-learned global model as the robot moves through its environment. Techniques are described for constructing a line segment description of the most recent sensor scan (the sensor model), and for integrating such descriptions to build up a model of the immediate environment (the composite local model). The estimated position of the robot is corrected by the difference in position between observed sensor signals and the corresponding symbols in the composite local model. A learning technique is described in which the robot develops a global model and a network of places. The network of places is used in global path planning, while the segments are recalled from the global model to assist in local path execution. This system is useful for navigation in a finite, pre-learned domain such as a house, office, or factory.
529 citations
Book•
01 Jul 1990
TL;DR: The CMU Rover as discussed by the authors is a more capable, and neatly operational, robot being built to develop and extend the Stanford Cart and to explore new directions, which is a remotely controlled TV-equipped mobile robot.
Abstract: The Stanford Cart was a remotely controlled TV-equipped mobile robot. A computer program was written which drove the Cart through cluttered spaces, gaining its knowledge of the world entirely from images broadcast by an on-board TV system. The CMU Rover is a more capable, and neatly operational, robot being built to develop and extend the Stanford work and to explore new directions. The Cart used several kinds of stereopsis to locate objects around it in three dimensions and to deduce its own motion. It planned an obstacle-avoiding path to a desired destination on the basis of a model built with this information. The plan changed as the Cart perceived new obstacles on its journey. The system was reliable for short runs, but slow. The Cart moved 1 m every 10 to 15 min, in lurches. After rolling a meter it stopped, took some pictures, and thought about them for a long time. Then it planned a new path, executed a little of it, and paused again. It successfully drove the Cart through several 20-m courses (each taking about 5 h) complex enough to necessitate three or four avoiding swerves; it failed in other trials in revealing ways. The Rover system has been designed with maximum mechanical and control system flexibility to support a wide range of research in perception and control. It features an omnidirectional steering system, a dozen on-board processors for essential real-time tasks, and a large remote computer to be helped by a high-speed digitizing/data playback unit and a high-performance array processor. Distributed high-level control software similar in organization to the Hearsay II speech-understanding system and the beginnings of a vision library are being readied. By analogy with the evolution of natural intelligence, we believe that incrementally solving the control and perception problems of an autonomous mobile mechanism is one of the best ways of arriving at general artificial intelligence.
415 citations
25 Mar 1985
TL;DR: The key idea is to use a relational map, which is rubbery and stretchy, rather than try to place observations in a 2-d coordinate system.
Abstract: Mobile robots sense their environment and receive error laden readings. They try to move a certain distance and direction, and do so only approximately. Rather than try to engineer these problems away it may be possible, and may be necessary, to develop map making and navigation algorithms which explicitly represent these uncertainties, but still provide robust performance. The key idea is to use a relational map, which is rubbery and stretchy, rather than try to place observations in a 2-d coordinate system.
224 citations