https://www.ida.liu.se/~729G12/mtrl/Anderson%20-%202003%20-%20Embodied%20Cognition.pdf

Embodied cognition: a field guide

The issues involved in integrating multiple sensors into the operation of a system are presented in the context of the type of information these sensors can uniquely provide. A survey is provided of the variety of approaches to the problem of multisensor integration and fusion that have appeared in the literature in recent years ranging from general paradigms, frameworks, and methods for integrating and fusing multisensory information to existing multisensor systems used in different areas of application. General multisensor fusion methods, sensor selection strategies, and world models are examined, along with approaches to the integration and fusion of information from combinations of different types of sensors. Short descriptions of the role of multisensor integration and fusion in the operation of a number of existing mobile robots are provided, together with proposed high-level multisensory representations suitable for mobile robot navigation and control. Existing multisensor systems for industrial and other applications are considered. >

Multisensor integration and fusion in intelligent systems

List of Figures. List of Tables. List of Abbreviations and Symbols. Preface. 1. Introduction. 2. A Sonar Sensor Model. 3. Model-Based Localization. 4. Map Building. 5. Simultaneous Map Building and Localization. 6. Directed Sensing Strategies. 7. Why Use Sonar? A. Hardware and Software. Bibliography. Index.

Directed Sonar Sensing for Mobile Robot Navigation

The principal components and capabilities of Blanche, an autonomous robot vehicle, are described. Blanche is designed for use in structured office or factory environments rather than unstructured natural environments, and it is assumed that an offline path planner provides the vehicle with a series of collision-free maneuvers, consisting of line and arc segments, to move the vehicle to a desired position. These segments are sent to a low-level trajectory generator and closed-loop motion control. The controller assumes accurate knowledge of the vehicle's position. Blanche's position estimation system consists of a priori map of its environment and a robust matching algorithm. The matching algorithm also estimates the precision of the corresponding match/correction that is then optimally (in a maximum-likelihood sense) combined with the current odometric position to provide an improved estimate of the vehicle's position. The system does not use passive or active beacons. Experimental results are reported. >

Blanche-an experiment in guidance and navigation of an autonomous robot vehicle

An architecture that integrates a map representation into a reactive, subsumption-based mobile robot is described. This fully integrated reactive system removes the distinction between the control program and the map. The method was implemented and tested on a mobile robot equipped with a ring of sonars and a compass, and programmed with a collection of simple, incrementally designed behaviors. The robot performs collision-free navigation, dynamic landmark detection, map construction and maintenance, and path planning. Given any known landmark as a goal, the robot plans and executes the shortest known path to it. If the goal is not reachable, the robot detects failure, updates the map, and finds an alternate route. The topological representation primitives are designed to suit the robot's sensors and its navigation behavior, thus minimizing the amount of stored information. Distributed over a collection of behaviors, the map itself performs constant-time localization and linear-time path planning. The approach is qualitative and robust. >

Integration of representation into goal-driven behavior-based robots

Research on mobile robots began in the late sixties with the Stanford Research Institute’s pioneering work. Two versions of SHAKEY, an autonomous mobile robot, were built in 1968 and 1971. The main purpose of this project was “to study processes for the realtime control of a robot system that interacts with a complex environment” 〈NIL 69〉. Indeed, mobile robots were and still are a very convenient and powerful support for research on artificial intelligence oriented robotics. They possess the capacity to provide a variety of problems at different levels of generality and difficulty in a large domain including perception, decision making, communication, etc., which all have to be considered within the scope of the specific constraints of robotics: on-line computing, cost considerations, operating ability, and reliability.

M. Vaisset

Papers

An integrated navigation and motion control system for autonomous multisensory mobile robots