Showing papers on "Mobile robot navigation published in 1997"

Mobile robot localization using landmarks

Abstract: We describe an efficient method for localizing a mobile robot in an environment with landmarks. We assume that the robot can identify these landmarks and measure their bearings relative to each other. Given such noisy input, the algorithm estimates the robot's position and orientation with respect to the map of the environment. The algorithm makes efficient use of our representation of the landmarks by complex numbers. The algorithm runs in time linear in the number of landmarks. We present results of simulations and propose how to use our method for robot navigation.

Mobile Robot Positioning - Sensors and Techniques

Abstract: : Exact knowledge of the position of a vehicle is a fundamental problem in mobile robot applications. In the search for a solution, researchers and engineers have developed a variety of systems, sensors, and techniques for mobile robot positioning. This paper provides a review of relevant mobile robot positioning technologies. The paper defines seven categories for positioning systems: (1) Odometry, (2) Inertial Navigation, (3) Magnetic Compasses, (4) Active Beacons, (5) Global Positioning Systems, (6) Landmark Navigation, and (7) Model Matching. The characteristics of each category are discussed and examples of existing technologies are given for each category. The field of mobile robot navigation is active and vibrant, with more great systems and ideas being developed continuously. For this reason the examples presented in this paper serve only to represent their respective categories; they do not represent a judgment by the authors. Many ingenious approaches can be found in the literature, although, for reasons of brevity, not all could be cited in this paper. The appendix contains a tabular comparison of the positioning systems discussed in this review that includes system and description, features, accuracy (position), accuracy (orientation), effective range, and source of information. (47 refs.)

The uses of fuzzy logic in autonomous robot navigation

Abstract: The development of techniques for autonomous navigation in real-world environments constitutes one of the major trends in the current research on robotics. An important problem in autonomous navigation is the need to cope with the large amount of uncertainty that is inherent of natural environments. Fuzzy logic has features that make it an adequate tool to address this problem. In this paper, we review some of the possible uses of fuzzy logic in the field of autonomous navigation. We focus on four issues: how to design robust behavior-producing modules; how to coordinate the activity of several such modules; how to use data from the sensors; and how to integrate high-level reasoning and low-level execution. For each issue, we review some of the proposals in the literature, and discuss the pros and cons of fuzzy logic solutions.

Vehicle location and navigation systems

Abstract: Introduction: Brief History. Modern Vehicle Location and Navigation References. Digital Map Database Module: Introduction. Basic Representations. Reference Coordinate Systems. Standards. Proprietary Digital Map Databases. Digital Map Compilation. Positioning Module: Dead Reckoning. Relative Sensors. Absolute Sensors. Sensor Fusion. Map-Matching Module: Conventional Map-Matching. Fuzzy-Logic-Based Map-Matching. Other Map-Matching Algorithms. Map-Aided Sensor Calibration. Route-Planning Module: Shortest Path. Heuristic Search. Bi-Directional Search. Hierarchical Search. Other Algorithms. Route Guidance Module: Guidance While En-Route. Guidance While Off-Route. Guidance With Dynamic Information. Human-Machine Interface Module: Visual-Display-Based Interfaces. Voice-Based Interfaces. Wireless Communications Module: Communication Subsystem Attributes. Existing Communications Technologies. Communications Subsystem Integration. Autonomous Location and Navigation: Vehicle Location. Vehicle Navigation. Centralized Location and Navigation: Automatic Vehicle Location. Dynamic Navigation. Applications -- Mayday. A Case Study -- ADVANCE: Traffic Information Center. Mobile Navigation Assistant. Communications Network. Initial Evaluation Results. Conclusions: Past Lessons. Future Directions. Appendices.

Sensor fusion for mobile robot navigation

Abstract: We review techniques for sensor fusion in robot navigation, emphasizing algorithms for self-location. These find use when the sensor suite of a mobile robot comprises several different sensors, some complementary and some redundant. Integrating the sensor readings, the robot seeks to accomplish tasks such as constructing a map of its environment, locating itself in that map, and recognizing objects that should be avoided or sought. The review describes integration techniques in two categories: low-level fusion is used for direct integration of sensory data, resulting in parameter and state estimates; high-level fusion is used for indirect integration of sensory data in hierarchical architectures, through command arbitration and integration of control signals suggested by different modules. The review provides an arsenal of tools for addressing this (rather ill-posed) problem in machine intelligence, including Kalman filtering, rule-based techniques, behavior based algorithms, and approaches that borrow from information theory, Dempster-Shafer reasoning, fuzzy logic and neural networks.

The autonomous mobile robot SENARIO: a sensor aided intelligent navigation system for powered wheelchairs

Abstract: The SENARIO project is develoing a sensor-aided intelligent navigation system that provides high-level navigational aid to users of powered wheelchairs. The authors discuss new and improved technologies developed within SENARIO concerning task/path planning, sensing and positioning for indoor mobile robots as well as user interface issues. The autonomous mobile robot SENARIO, supports semi- or fully autonomous navigation. In semi-autonomous mode the system accepts typical motion commands through a voice-activated or standard joystick interface and supports robot motion with obstacle/collision avoidance features. Fully autonomous mode is a superset of semi-autonomous mode with the additional ability to execute autonomously high-level go-to-goal commands. At its current stage, the project has succeeded in fully supporting semi-autonomous navigation, while experiments on the fully autonomous mode are very encouraging.

Stereo vision based mapping and navigation for mobile robots

Abstract: This paper describes a visually guided robot that can plan paths, construct maps and explore an indoor environment. The robot uses a trinocular stereo vision system to produce highly accurate depth images at 2 Hz allowing it to safely travel through the environment at 0.5 m/s. The algorithm integrates stereo vision, occupancy grid mapping, and potential field path planning techniques to form a robust and cohesive robotic system for mapping and navigation. Stereo vision is shown to be a viable alternative to active sensing devices such as sonar and laser range finders.

A navigation/guidance system for a land-based vehicle

Abstract: A navigation/guidance system (10) uses a dead reckoning navigator with periodic GPS fixes to correct the drift of the inertial system. The navigation system (10) primarily uses speed sensed by Doppler radar (30) and attitude and heading sensed by a set of gyros (24). The navigation system (10) uses various processes to compensate for any sensor errors. The system uses attitude data to compensate for GPS leverarm errors. The system can be used on a land-based vehicle (60) to economically and accurately provide navigation data.

Active mobile robot localization

Abstract: Localization is the problem of determining the position of a mobile robot from sensor data. Most existing localization approaches are passive, i.e., they do not exploit the opportunity to control the robot’s effectors during localization. This paper proposes an active localization approach. The approach provides rational criteria for (1) setting the robot’s motion direction (exploration), and (2) determining the pointing direction of the sensors so as to most efficiently localize the robot. Furthermore, it is able to deal with noisy sensors and approximative world models. The appropriateness of our approach is demonstrated empirically using a mobile robot in a structured office environment.

Building a global map of the environment of a mobile robot: the importance of correlations

Abstract: The work presented in this paper is aimed at evaluating the influence of correlations between map entities on the process of robot relocation and global map building of the environment of a mobile robot navigating in an indoor environment. An EKF filter approach, supported by a probabilistic model to represent uncertain geometric information, is used to process the information obtained by the sensors mounted on the robot. We have developed two approaches, first, considering the existence of correlations, and second assuming independence between entities of the map. We have experimented with the mobile robot MACROBE, using its laser rangefinder.

Fuzzy Maps: A New Tool for Mobile Robot Perception and Planning

Abstract: An essential component of an autonomous mobile robot is the exteroceptive sensory system. Sensing capabilities should be integrated with a method for extracting a representation of the environment from uncertain sensor data and with an appropriate planning algorithm. In this article, fuzzy logic concepts are used to introduce a tool useful for robot perception as well as for planning collision-free motions. In particular, a map of the environment is defined as the fuzzy set of unsafe points, whose membership function quantifies the possibility for each point to belong to an obstacle. The computation of this set is based on a specific sensor model and makes use of intermediate sets generated from range measures and aggregated by means of fuzzy set operators. This general approach is applied to a robot with ultrasonic rangefinders. The resulting map building algorithm performs well, as confirmed by a comparison with stochastic methods. The planning problem on fuzzy maps can be solved by defining various path cost functions, corresponding to different strategies, and by searching the map for optimal paths. To this end, proper instances of the A* algorithm are devised. Experimental results for a Nomad 200™ robot moving in a real-world environment are presented. © 1997 John Wiley & Sons, Inc.

Autonomous mobile robot system for sensor-based and map-based navigation in pipe networks

Abstract: The autonomous mobile robot system is provided with a sensor-based and map-based navigation system for navigating in a pipe network. The navigation is based on the classification of pre-existing natural landmarks. The navigation system can compensate for inaccurate robot system's motion control, sensor information, and landmark classification.

Learning view graphs for robot navigation

Abstract: We present a purely vision-based scheme for learning a topological representation of an open environment. The system represents selected places by local views of the surrounding scene, and finds traversable paths between them. The set of recorded views and their connections are combined into a graph model of the environment. To navigate between views connected in the graph, we employ a homing strategy inspired by findings of insect ethology. In robot experiments, we demonstrate that complex visual exploration and navigation tasks can thus be performed without using metric information.

Application of radio frequency identification devices to support navigation of autonomous mobile robots

Abstract: Autonomous mobile robots are expected to be a solution for a vast of applications in service and industry applications. However, a great and still unsolved problem for most environments and applications is the robust and cheap positioning, i.e. the determination of the robot's current position. A navigation system is presented, that is based on the use of radio frequency identification (RFID) as artificial landmark system. In combination with the presented behavior based control architecture this system enables the robot to reach any reachable landmark in its environment through a topological robot positioning approach. A technique called re-classification (which depends on the special features and advantages of RFID systems) is presented that makes it possible to determine the robot's exact global position in presence of a landmark. Based on this accurate position (i.e. its coordinates) the robot can reach an arbitrary goal specified by coordinates even if it is not marked with a RFID landmark.

Socially embedded learning of the office-conversant mobile robot Jijo-2

Abstract: This paper explores a newly developing direction of machine learning called ''socially embedded learning". In this research we have been building an office-conversant mobile robot which autonomously moves around in an office environment, actively gathers information through close interaction wi th this environment including sensing multi-modal data and making dialog with people in the office, and acquires knowledge about the environment wi th which it ultimately becomes conversant. Here our major concerns are in how the close interaction between the learning system and its social environment can help or accelerate the systems learning process, and what kinds of prepared mechanisms are necessary for the emergence of such interactions. The office-conversant robot is a platform on which we implement our ideas and test their feasibility in a real-world setting. An overview of the system is given and two examples of implemented ideas, i.e. dialog-based map acquisition and route acquisition by following, are described in detail.

Active mobile robot localization by entropy minimization

Abstract: Localization is the problem of determining the position of a mobile robot from sensor data. Most existing localization approaches are passive, i.e., they do not exploit the opportunity to control the robot's effecters during localization. This paper proposes an active localization approach. The approach provides rational criteria for (1) setting the robot's motion direction (exploration), and (2) determining the pointing direction of the sensors so as to most efficiently localize the robot. Furthermore, it is able to deal with noisy sensors and approximate world models. The appropriateness of our approach is demonstrated empirically using a mobile robot in a structured office environment.

Applying genetic programming to evolve behavior primitives and arbitrators for mobile robots

Abstract: The behavior-based approach has been successfully applied to designing robot control systems. This paper presents our work, based on evolutionary algorithms, to program behavior-based robots automatically. Instead of hand-coding all the behavior controllers or evolving an entire control system for an overall task, we suggest our approach at the intermediate level: it includes evolving behavior primitives and behavior arbitrators for a mobile robot to achieve the specified tasks. To examine the developed approach, we evolve a control system for a moderately complicated box-pushing task as an example. We first evolved the controllers in a simulation and then transferred them to the Khepera miniature robot. Experimental results show the promise of our approach, and the evolved controllers are transferred to the real robot without loss of performance.

A cooperative multi-agent system and its real time application to robot soccer

Abstract: The soccer robot system consists of multi agents, with highly coordinated operation and movements so as to fulfill specific objectives, even under adverse situation. The coordination of the multi-agents is associated with a lot of supplementary work in advance. The associated issues are the position correction, prevention of communication congestion, local information sensing in addition to the need for imitating the human-like decision making. A control structure for a soccer robot is designed and several behaviors and actions for a soccer robot are proposed. Modified zone defense as a basic strategy and several special strategies for fouls are applied to SOTY and MIRO teams for MIROSOT (Micro-Robot World Cup Soccer Tournament).

Xavier: experience with a layered robot architecture

Abstract: Office delivery robots have to perform many tasks such as picking up and delivering mail or faxes, returning library books, and getting coffee. They have to determine the order in which to visit locations, plan paths to those locations, follow paths reliably, and avoid static and dynamic obstacles in the process. Reliability and efficiency are key issues in the design of such autonomous robot systems. They must deal reliably with noisy sensors and actuators and with incomplete knowledge of the environment. They must also act efficiently, in real time, to deal with dynamic situations. To achieve these objectives, we have developed a robot architecture that is composed of four layers: obstacle avoidance, navigation, path planning, and task planning. The layers are independent, communicating processes that are always active, processing sensory data and status information to update their decisions and actions. A version of our robot architecture has been in nearly daily use in our building since December 1995. As of January 1997, the robot has traveled more than 110 kilometers (65 miles) in service of over 2500 navigation requests that were specified using our World Wide Web interface.

Adaptive navigation of mobile robots with obstacle avoidance

Abstract: A local navigation technique with obstacle avoidance, called adaptive navigation, is proposed for mobile robots in which the dynamics of the robot are taken into consideration. The only information needed about the local environment is the distance between the robot and the obstacles in three specified directions. The navigation law is a first-order differential equation and navigation to the goal and obstacle avoidance are achieved by switching the direction angle of the robot. The effectiveness of the technique is demonstrated by means of simulation examples.

A distributed algorithm for cooperative navigation among multiple mobile robots

Abstract: The navigation capability of a group of robots can be improved by sensing of relative inter-robot positions and intercommunication of position estimates and planned trajectories. The cooperative navigation system (CNS) algorithm described here is based on a Kalman filter which uses inter-robot position sensing to update the collective position estimates of the group. Assuming independence of sensing and positioning errors, the CNS algorithm always improves individual robot estimates and the collective navigation performance improves as the number of robots increases. The CNS algorithm computation may be distributed among the robot group. Simulation results and experimental measurements on two Yamabico robots are described.

A mobile robot that learns its place

Abstract: We show how a neural network can be used to allow a mobile robot to derive an accurate estimate of its location from noisy sonar sensors and noisy motion information. The robot's model of its locat...

Visual navigation in an open environment without map

Abstract: We describe how a mobile robot controlled only by visual information can retrieve a particular goal location in an open environment. Our model does not need a precise map nor to learn all the possible positions in the environment. The system is a neural architecture inspired from neurobiological studies using the recognition of visual patterns called landmarks. The robot merges this visual information and its azimuth to build a plastic representation of its location. This representation is used to learn the best movement to reach the goal. A simple and fast online learning of a few places located near the goal allows the robot to reach the goal from anywhere in its neighborhood. The system uses only an egocentric representation of the robot environment and presents very high generalization capabilities. We describe an efficient implementation tested on our robot in two real indoor environments. We show the limitations of the model and its possible extensions to create autonomous robots only guided by visual information.

Distributed vision system: a perceptual information infrastructure for robot navigation

Abstract: This paper proposes a Distributed Vision System as a Perceptual Information Infrastructure for robot navigation in a dynamically changing world. The distributed vision system, consisting of vision agents connected with a computer network, monitors the environment, maintains the environment models, and actively provides various information for the robots by organizing communication between the vision agents. In addition to conceptual discussions and fundamental issues, this paper provides a prototype of the distributed vision system for navigating mobile robots.

Mobile robot navigation using artificial landmarks

Abstract: This article describes a landmark-based navigation technique for a mobile robot. Robot position estimation is achieved by using a camera and a navigational landmark pattern, which consists of simple geometrical patterns. The Modified Elliptical Hough Transform (MEHT) is developed for detecting and measuring the projection of the landmark in the camera's image space. Robustness of this approach is demonstrated by studying the cases of noisy image data and partial occlusion of the landmark pattern. Error analysis of MEHT is performed to provide more understanding of the effects of applying elliptical approximation to the projection of a circular pattern. © 1997 John Wiley & Sons, Inc.