A Distributed Model For Mobile Robot Environment Learning And Navigation

A distributed method for mobile robot navigation, spatial learning, and path planning is presented. It is implemented on a sonar-based physical robot, Toto, consisting of three competence layers: 1) Low-level navigation: a collection of reflex-like rules resulting in emergent boundary-tracing. 2) Landmark detection: dynamically extracts landmarks from the robot's motion. 3) Map learning: constructs a distributed map of landmarks. The parallel implementation allows for localization in constant time. {\it Spreading of activation} computes both topological and physical shortest paths in linear time. The main issues addressed are: distributed, procedural, and qualitative representation and computation, emergent behaviors, dynamic landmarks, minimized communication.

Fifty years ago, A. Turing predicted that by 2000 we would have a machine that could pass the Turing test. Although this may not yet be true, AI has advanced signi?cantly in these 50 years, and at the dawn of the XXI century is still an activeandchallenging?eld.Thisyearisalsosigni?cantforAIinMexico,withthe merging of the two major AI conferences into the biennial Mexican International Conference on Arti?cial Intelligence (MICAI) series. MICAI is the union of the Mexican National AI Conference (RNIA) and the International AI Symposium (ISAI), organized annually by the Mexican Society forAI(SMIA,since1984)andbytheMonterreyInstituteofTechnology(ITESM, since1988),respectively.The?rstMexicanInternationalConferenceonArti?cial Intelligence, MICAI 2000, took place April 11-14, 2000, in the city of Acapulco, Mexico.ThisconferenceseekstopromoteresearchinAI,andcooperationamong Mexican researchers and their peers worldwide. We welcome you all. Over 163 papers from 17 di?erent countries were submitted for consideration to MICAI 2000. After reviewing them thoroughly, MICAI’s program committee, referees, and program chair accepted 60 papers for the international track. This volume contains the written version of the papers and invited talks presented at MICAI. We would like to acknowledge the support of the American Association for Arti?cial Intelligence (AAAI), and the International Joint Conference on Art- cial Intelligence (IJCAI). We are specially grateful for the warm hospitality and generosity o?ered by the Acapulco Institute of Technology.

Many difficult scientific discovery tasks can only be solved in interactive ways, by combining intelligent computing techniques with intuitive and adaptive user interfaces. It is inevitable to use human intelligence in scientific discovery systems: human eyes can capture complex patterns and relationships, along with detecting the exceptional cases in a data set; the human brain can easily manipulate perceptions to make decisions. Ambient intelligence is about this kind of ubiquitous and autonomous human interaction with information. Scientific discovery is a process of creative perception and communication, dealing with questions like: how do we significantly reduce information while maintaining meaning, or how do we extract patterns from massive data and growing data resources. Originating from the SIGCHI Workshop on Ambient Intelligence for Scientific Discovery, this state-of-the-art survey is organized in three parts: new paradigms in scientific discovery, ambient cognition, and ambient intelligence systems. Many chapters share common features such as interaction, vision, language, and biomedicine.

This book includes a selection of research work in the mobile robotics area, where several interesting topics are presented. In this way we find a review of multi-agents, different techniques applied to the navigation systems, artificial intelligence algorithms, which include deep learning applications, systems where a Kalman filter estimator is extended for visual odometry, and finally the design of an on-chip system for the execution of cognitive agents. Additionally, the development of different ideas in mobile robot applications are included and hopefully will be useful and enriching for readers.

Originally published in 1995, this volume is the direct result of a conference in which a number of leading researchers from the fields of artificial intelligence and biology gathered to examine whether there was any ground to assume that a new AI paradigm was forming itself and what the essential ingredients of this new paradigm were. A great deal of scepsis is justified when researchers, particularly in the cognitive sciences, talk about a new paradigm. Shifts in paradigm mean not only new ideas but also shifts in what constitutes good problems, what counts as a result, the experimental practice to validate results, and the technological tools needed to do research. Due to the complexity of the subject matter, paradigms abound in the cognitive sciences -- connectionism being the most prominent newcomer in the mid-1980s. This workshop group was brought together in order to clarify the common ground, see what had been achieved so far, and examine in which way the research could move further. This volume is a reflection of this important meeting. It contains contributions which were distributed before the workshop but then substantially broadened and revised to reflect the workshop discussions and more recent technical work. Written in polemic form, sometimes criticizing the work done thus far within the new paradigm, this collection includes research program descriptions, technical contributions, and position papers.

This pioneering book describes the development of a robot mapping and navigation system inspired by models of the neural mechanisms underlying spatial navigation in the rodent hippocampus. Computational models of animal navigation systems have traditionally had limited performance when implemented on robots. This is the first research to test existing models of rodent spatial mapping and navigation on robots in large, challenging, real world environments.

It has long been the goal of engineers to develop tools that enhance our ability to do work, increase our quality of life, or perform tasks that are either beyond our ability, too hazardous, or too tedious to be left to human efforts. Autonomous mobile robots are the culmination of decades of research and development, and their potential is seemingly unlimited. Roadmap to the Future Serving as the first comprehensive reference on this interdisciplinary technology, Autonomous Mobile Robots: Sensing, Control, Decision Making, and Applications authoritatively addresses the theoretical, technical, and practical aspects of the field. The book examines in detail the key components that form an autonomous mobile robot, from sensors and sensor fusion to modeling and control, map building and path planning, and decision making and autonomy, and to the final integration of these components for diversified applications. Trusted Guidance A duo of accomplished experts leads a team of renowned international researchers and professionals who provide detailed technical reviews and the latest solutions to a variety of important problems. They share hard-won insight into the practical implementation and integration issues involved in developing autonomous and open robotic systems, along with in-depth examples, current and future applications, and extensive illustrations. For anyone involved in researching, designing, or deploying autonomous robotic systems, Autonomous Mobile Robots is the perfect resource.

Until the mid-1980s, AI researchers assumed that an intelligent system doing high-level reasoning was necessary for the coupling of perception and action. In this traditional model, cognition mediates between perception and plans of action. Realizing that this core AI, as it was known, was illusory, Rodney A. Brooks turned the field of AI on its head by introducing the behavior-based approach to robotics. The cornerstone of behavior-based robotics is the realization that the coupling of perception and action gives rise to all the power of intelligence and that cognition is only in the eye of an observer. Behavior-based robotics has been the basis of successful applications in entertainment, service industries, agriculture, mining, and the home. It has given rise to both autonomous mobile robots and more recent humanoid robots such as Brooks' Cog. This book represents Brooks' initial formulation of and contributions to the development of the behavior-based approach to robotics. It presents all of the key philosophical and technical ideas that put this "bottom-up" approach at the forefront of current research in not only AI but all of cognitive science.