Showing papers on "Mobile robot navigation published in 1992"

Directed Sonar Sensing for Mobile Robot Navigation

Abstract: 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.

Integration of representation into goal-driven behavior-based robots

Abstract: 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. >

Dynamic map building for an autonomous mobile robot

Abstract: This article presents an algorithm for autonomous map building and maintenance for a mobile robot. We believe that mobile robot navigation can be treated as a problem of tracking ge ometric features that occur naturally in the environment. We represent each feature in the map by a location estimate (the feature state vector) and two distinct measures of uncertainty: a covariance matrix to represent uncertainty in feature loca tion, and a credibility measure to represent our belief in the validity of the feature. During each position update cycle, pre dicted measurements are generated for each geometric feature in the map and compared with actual sensor observations. Suc cessful matches cause a feature's credibility to be increased. Unpredicted observations are used to initialize new geometric features, while unobserved predictions result in a geometric feature's credibility being decreased. We describe experimental results obtained with the algorithm that demonstrate successful map building using real son...

Cooperation without communication: Multiagent schema‐based robot navigation

Abstract: Multiagent robotics affords the opportunity to solve problems more efficiently and effectively than any single agent could achieve. Nonetheless, communication bottlenecks between agents pose potentially serious drawbacks in coordinated behavior. In this research, we demonstrate the efficiency of multiagent schema-based navigation for object retrieval. Primitive motor behaviors are specified for each of the individual robotic agents, which produce safe task-achieving action in an unstructured environment. When implemented over several identical units, retrieval is facilitated in the absence of interagent communication as evidenced by spontaneous recruitment of several agents to accomplish a task. Simulation results are provided to demonstrate these effects. Extensions to other task-achieving behaviors are also feasible.

SSS: a hybrid architecture applied to robot navigation

Abstract: Describes a three-layer architecture, SSS, for robot control. It combines a servo-control layer, a subsumption layer, and a symbolic layer in a way that allows the advantages of each technique to be fully exploited. The key to this synergy is the interface between the individual subsystems. The design of situation recognizers that bridge the gap between the servo and subsumption layers, and event detectors that link the subsumption layers and symbolic layers are discussed. The development of such a combined system is illustrated by a fully implemented indoor navigation example. The resulting robot was able to automatically map office building environments, and smoothly navigate through them at the rapid speed of 2.6 feet per second. >

Fast vision-guided mobile robot navigation using model-based reasoning and prediction of uncertainties

Abstract: The model-based vision system described in this paper allows a mobile robot to navigate indoors at an average speed of 8 to 10 m/min using ordinary laboratory computing hardware of approximately 16 MIPS power. The navigation capabilities of the robot are not impaired by the presence of stationary or moving obstacles. The vision system maintains a model of uncertainty and keeps track of the growth of uncertainty as the robot travels toward the goal position. The estimates of uncertainty are then used to predict bounds on the locations and orientations of landmarks expected to be seen in a monocular image. This greatly reduces the search for establishing correspondence between the features visible in the image and the landmarks. Given a sequence of image features and a sequence of landmarks derived from a geometric model of the environment, a special aspect of our vision system is the sequential reduction in the uncertainty as each image feature is matched successfully with a landmark, allowing subsequent features to be matched more easily; this is a natural by-product of the manner in which we use Kalman filter-based updating.

Fast Vision-guided Mobile Robot Navigation Using Model-based Reasoning And Prediction Of Uncertainties

Abstract: The model-based vision system described in this thesis allows a mobile robot to navigate indoors at an average speed of 8 meters/minute using ordinary laboratory computing hardware of approximately 16 MIPS power. The navigation capabilities of the robot are not impaired by the presence of the stationary or moving obstacles. The vision system maintains a model of uncertainty and keeps track of the growth of uncertainty as the robot travels towards the goal position. The estimates of uncertainty are then used to predict bounds on the locations and orientations of landmarks expected to be seen in a monocular image. This greatly reduces the search for establishing correspondence between the features visible in the image and the landmarks. Given a sequence of image features and a sequence of landmarks derived from a geometric model of the environment, a special aspect of our vision system is the sequential reduction in the uncertainty as each image feature is matched successfully with a landmark, allowing subsequent features to be matched more easily, this being a natural byproduct of the manner in which we use Kalman-filter based updating. Strategies for path planning, path replanning and perception planning are introduced for the robot to navigate in the presence of obstacles. Finally, experimental results are presented.

Navigation apparatus for vehicles

Abstract: A navigation apparatus for vehicles according to the present invention has a display device for displaying road information. The navigation system is designed to selectively display the road information which is close to the current position of the vehicle and/or the demands of the driver from a large amount of road information (each of which consists of image data to be displayed and logical data on which logical determination can be made).

Error correction in mobile robot map learning

Abstract: An issue that must be addressed in map-learning systems is that of error accumulation. The primary emphasis in the literature has been on reducing errors entering the map. The authors suggest that this methodology must reach a point of diminishing returns, and hence focus on explicit error detection and correction. By identifying the possible types of mapping errors, structural constraints can be exploited to detect and diagnose mapping errors. Such robust mapping requires little overhead beyond that needed for nonrobust mapping. A mapping system was implemented based on those ideas. Extensive testing in simulation demonstrated the effectiveness of the proposed error-correction strategies. >

Path planning for a mobile robot

Abstract: Two problems for path planning of a mobile robot are considered. The first problem is to find a shortest-time, collision-free path for the robot in the presence of stationary obstacles in two dimensions. The second problem is to determine a collision-free path (greedy in time) for a mobile robot in an environment of moving obstacles. The environment is modeled in space-time and the collision-free path is found by a variation of the A* algorithm. >

Image-based homing

Abstract: A system that allows a robot to use a model of its environment to navigate is reported. The system maps the environment as a set of snapshots of the world taken at target locations. The robot uses an image-based local homing algorithm to navigate between neighboring and target locations. The approach has an imaging system that acquires a compact, 360 degrees representation of the environment as an intensity waveform, and an image-based, qualitative homing algorithm that allows the robot to navigate without explicitly inferring three-dimensional structure from the image. The result of an experiment in a typical indoor environment are reported. They show that image-based navigation is a feasible alternative to approaches using 3-D models and more complex model-based vision algorithms. >

Landmark-based robot navigation

Abstract: To operate in the real world robots must deal with errors in control and sensing. Achieving goals despite these errors requires complex motion planning and plan monitoring. We present a reduced version of the general problem and a complete planner that solves it in polynomial time. The basic concept underlying this planner is that of a landmark. Within the field of influence of a landmark, robot control and sensing are perfect. Outside any such field control is imperfect and sensing is null. In order to make sure that the above assumptions hold, we may have to specifically engineer the robot workspace. Thus, for the first time, workspace engineering is seen as a means to make planning problems tractable. The planner was implemented and experimental results are presented. An interesting feature of the planner is that it always returns a universal plan in the form of a collection of reaction rules. This plan can be used even when the input problem has no guaranteed solution, or when unexpected events oceur during plan execution.

Navigation system for a mobile robot

Abstract: A navigation system for a mobile autonomous robot that includes apparatus for creating and maintaining a map of an environment the mobile autonomous robot is to traverse including provision for storing in a map at an assigned location features representative of geometric beacons located in the environment. Because of the uncertainty in its sensor's operating conditions and changes in the environment, a credibility measure is associated with each map feature stored. This credibility measure is increased or decreased whenever the map feature assigned to a location matches or does not match, respectively, a geometric beacon corresponding to such location. Whenever a geometric beacon is observed for a location that does into match a previously stored map features, an appropriate map feature is added for such location.

Coordinating Autonomous And Centralized Decision Making To Achieve Cooperative Behaviors Between Multiple Mobile Robots

Abstract: The problem of organizing a multiple autonomous mobile robot system is considered. At any moment, the behavior of each robot, in a multi robot society, is in one of two phases either; (1)working for its own purpose, or (2)working for a common purpose with one or more other robots. In situation(l), the robot operates under its own decision making using the principle of modest cooperation. In situation(2), each robot does not make its own decisions, instead one robot is selected as a leader and decides the behavior of all the concerned robots. While the multi robot system is functioning, each robot will be switching its decision making mode, between the autonomous and the centralized methods. In this way, the coordinated behaviors of the multiple autonomous robots can be easily designed and achieved .

Behavior-based robot navigation for extended domains

Abstract: Behavior-based robotic systems have been successfully deployed for a wide range of planar ground-based tasks. This article describes how reactive (behavior-based) systems can be applied to new and more difficult target domains. ln particular, schema-based navigation is shown to be both feasible and useful in two new areas: three-dimensional navigation for use in aerospace and undersea applications, and "two and one-half"-dimensional surroundings for outdoor navigation in rough terrain. Extensive simulation studies demonstrate the utility of this approach in both cases.

Handling real-world motion planning: a hospital transport robot

Abstract: A description is given of a hospital transport mobile robot, HelpMate, developed to carry out such tasks as the delivery of off-schedule meal trays, lab and pharmacy supplies, and patient records. Unlike many existing delivery systems in the industry which operate within a rigid network of wires buried or attached to the floor, a hospital transport robot is expected to be able to navigate much like a human would, including handling uncertainty and unexpected obstacles. The navigation system of HelpMate makes use of the specific structure of a hospital hallway environment and relies on recent results on provable sensor-based motion planning algorithms that specifically address the issue of navigation in an unknown and unstructured environment. Also incorporated in the system are algorithms for handling unmodeled factors such as sensor noise and sensor inaccuracy, errors in position estimation, and moving obstacles (e.g. people). >

Adaptive State Space Quantisation For Reinforcement Learning Of collision-free navigation

Abstract: The paper describes a self-learning control system for a mobile robot. Based on sensor information the control system has to provide a steering signal in such a way that collisions are avoided. Since in our case no ‘examples’ are available, the system learns on the basis of an external reinforcement signal which is negative in case of a collision and zero otherwise. Rules from Temporal Difference learning are used to find the correct mapping between the (discrete) sensor input space and the steering signal. We describe the algorithm for learning the correct mapping from the input (state) vector to the output (steering) signal, and the algorithm which is used for a discrete coding of the input state space. keywords: reinforcement learning, neural networks, state-space quantisation, mobile robot navigation.

Autonomous navigation of a mobile robot using custom-designed qualitative reasoning VLSI chips and boards

Abstract: Two types of computer boards including custom-designed VLSI chips have been developed to add a qualitative reasoning capability to the real-time control of autonomous mobile robots. The design and operation of these boards are first described, and an example of their use for the autonomous navigation of a mobile robot is presented. The development of qualitative reasoning schemes emulating human-like navigation in a priori unknown environments is discussed. The efficiency of such schemes, which can consist of as little as a dozen qualitative rules, is illustrated in experiments involving an autonomous mobile robot navigating on the basis of very sparse and inaccurate sensor data. >

Sensory uncertainty field for mobile robot navigation

Abstract: The authors introduce an approach to motion planning with uncertainty for mobile robots. Given a model of the robot's environment, a sensory uncertainty field (SUF) is computed over the robot's configuration space. At every configuration q, the SUF is an estimate of the uncertainty in the sensed configuration that would be computed by matching the data given by the robot sensors against the environment model, if the robot was at the configuration q. A planner then makes use of the computed SUF to generate paths that minimize the expected errors. The computation of a SUF is described for a classical line-striping camera/laser range sensor. An implemented SUF-based motion planner for a robot equipped with this sensor is presented. >

A Sensor-based Obstacle Avoidance Controller For A Mobile Robot Using Fuzzy Logic And Neural Network

Abstract: Abslmct-This paper proposes a sensor-based path planning method which utilizcs fuzzy logic and neural network for obstacle avoidancc of a mobile robot in uncertain environments. In order to acquire the information about the environment around the mobile robot, the ultrasonic sensors mounted on the front of mobile robot are used. The neural network, whose inputs arc preprocessed by ultrasonic sensor readings, informs the mobile robot of the situation of environment in which mobile robot is at the present instant. Then, according to the situatiou class, the fuzzy rules are fired to make a decision on the mobilc robot action. This structure has a merit that the fuzzy rules €or obstacle avoidance can be easily constructed for more cornplcx environments. In addition, this method can be implcrncoted real time sincc the number of fuzzy rules used to avoid the obstacles is small. The fuzzy rules are constructed based on the human reasoning and are tuned by iterative simulations. The cffectivcness of the proposed avoidance method is vcrilicd by a series of simulations. Path planning is one of tlie most vital task in navigation of autonomous niobiic robot. Path planning for mobile robot may be tlivitletl illto two categories: One is the global path planning based on a priori complete inforniation about the environment antl the other is the local path pliinning based on sensory information i n uncertain environnient where the size, shape and loc,atioii of ol)stacles are UllIi1lo\v11. nietliotl incliitlcs configuration space Voronoi diiigraiii[2] and potential field out i n oft-line iii:aiinc:r. 1-Iowever, this metliod is not suitable for ntivigiition i n coiiiples and dynamically changing environment where uiiliiiown obstacles niiiy be located on a priori planned path. Thus, this inc~thotl niust be followed by sensor-based local path planning, so ciilletl obstacle avoidance, carried out in on-line nianncr. Local pittli plxnning utilizes tlie information provided by sensor suc,li as ultrasonic sensor, vision, laser range finder, proximity sensor and binnper switch R.A.Brooks[4] applied tlie for(;c-fielti concept to obstacle avoidance problem for mobile robot equipped with ultrasonic, sensors whose readings are used to compute the I-esultant repulsive force. Borenstein and I

Wall-following control of a mobile robot

Abstract: The wall-following control problem is characterized by moving the robot along a wall in a desired direction while maintaining a constant distance to that wall. From ultrasonic distance measurements the distance and the orientation of the robot with respect to the wall can be calculated. This is solved by the use of an observer: the distance and orientation are estimated using a robot model and corrected by sensor measurements. Since a wall may not be available continuously (e.g., an open door), the robot must be able to navigate on its dead-reckoning as well. The feedback controller has been set up in such a way that it can handle both the observer data and dead-reckoning data. The controller has been verified by means of experiments. The results show a good performance with an absolute error of a few millimeters from the desired distance to the wall. >

Sfx: An Architecture For Action-oriented Sensor Fusion

Abstract: Sensor fusion has an important role in the navigation of autonomous mobile robots. Our research has generated a generic and robust pro- cess model based on the action-oriented percep- tion paradigm. The autonomous execution and ex- ception handling abilities of this model have been implemented as the Sensor Fusion Effects (SFX) architecture. The key aspects of this implemen- tation are the sensing plan, the uncertainty man- agement mechanism, the application of feedback from the sensing process to individual sensors, the detection of exceptions to the sensing plan, and handling of those exceptions. This paper gives an overview of the SFX architecture, concentrating on the sensing plan as the central control struc- ture guiding autonomous execution. This paper also reports on experiments using sensor data col- lected from our mobile robot which demonstrate the use of the sensing plan representation, the ex- ecution sequence, the application of feedback, and how feedback improves the overall sensing capa- bilities of the robot.

Cooperation between man and robot: interface and safety

Abstract: The question of robot safety become increasingly important as future robots will be required to share their working area with humans in order to achieve a fruitful cooperation. The robot's contribution could be restricted to the laborious and repetitive work, whereas the human acts as a supervisor and handles exceptions. A new safety system has been developed which allows such a close interaction. One module has the task to localize people inside the working area and provide the robot with an appropriate behavior pattern in order to avoid situations endangering the operator. This module uses a camera and computer vision techniques to obtain the location of the operator. The other module of the safety system has to prevent a robot runaway, which can be defined as an unexpected robot motion due to a failure of robot hardware or software. Speech recognition is used as interface between operator and robot. A dedicated robot-control structure has been implemented permitting a fast and safe intervention of the operator by means of the speech system. >

Mobile Robot Navigation In A Dynamic World Using An Unsteady Diffusion Equation Strategy

Abstract: This paper discusses a method for map and sensorbased planning and execution, i.e. navigation, of smooth collision-free robot motion paths. Application of an unsteady diffusion equation model to path planning in a time-varying world distinguishes this approach from prior work in the field. Collision-free robot paths between a start and a mission dependent goal point are generated very rapidly by on-line simulation of a diffusion process and by repetitively evaluating the gradient of the computed concentration distribution functions. Related numerical algorithms are appropriate for implementation on a massively parallel distributed processor architecture. This paper describes application of the approach to various scenarios of robot vehicle navigation. Results of a field experiment performed with the mobile robot MACROBE are presented.

Using Custom-designed Vlsi Fuzzy Inferencing Chips For The Autonomous Navigation Of A Mobile Robot

Abstract: An approach merging the concepts of fuzzy logic and sensor-based behaviors has been developed to add a qualitative reasoning capability to the real-time control of autonomous mobile robots. The approach is implemented using custom-designed computer boards which include recently developed VLSI fuzzy inferencing chips. The design and operation of these boards are first described and an example of their use for the autonomous navigation of a mobile robot is presented. The development of qualitative reasoning schemes emulating human- like navigation in a-priori unknown environments is discussed. The approach using superposition of elemental sensor-based behaviors expressed in the fizzy Sets theoretic framework is shown to allow easy development and testing of the inferencing rule base, while providing for progressive addition of behaviors to resolve situations of increasing complexity. The efficiency of such schemes, which can consist of as little as a dozen qualitative rules, is illustrated in experiments involving an autonomous mobile robot navigating on the basis of very sparse and inaccurate sensor data.

Autonomous driving on a road network

Abstract: In order to drive a vehicle without manual intervention, short range information about the visible surrounding in front of the vehicle is extracted by machine vision: a fast, region-based tracking of lane boundaries and-at a lower frequency-an evaluation of the entire video imag in order to detect intersections. This is combined with internal map-based knowledge about the road network, which is supplied by the navigation system Travelpilot, commercially offered by Robert Bosch GmbH. The modules have been integrated into an experimental vehicle. Given a desired goal-position on a suitable selected road network, the vehicle is able to perform the necessary driving mission autonomously. >

Architecture of behavior-based mobile robot in dynamic environment

Abstract: The authors are developing a compact cart-type robot system which moves around an office. They propose a behavior-based architecture with three clustered (reflexive, purposive, and adaptive) agents that realizes efficiency in attaining the mission of the robot, and robustness against the various kinds of failures that may occur in a dynamic environment. The reflexive-level group consists of agents with contact, infrared, and ultrasonic sensors which maintain minimal safety of the robot. The role of the purposive-level group is to achieve the global mission of the robot, such as 'if the robot detects a small fire in the office, find and reach a fire extinguisher as soon as possible'. The adaptive-level group stands by to recover from failure in the purposive-level group or in a deadlock situation. Experimental results showed the effectiveness of the method. >

Planning Of Landmark Measurement For The Navigation A Mobile Robot

Abstract: Recognition of its current location is im- portant for a mobile robot to follow a planned path. Landmarks, which are assumed in the environment around the robot, are used to support this recognition. In this paper we propose a method for the robot to select the most suitable landmark among the measur- able landmarks from its current position by evaluating the error covariance update of the position estimation. We use the extended Kalman filter to update the po- sition estimation. We show the update behaviors of two types of landmarks : line type and point type. For the criteria of the evaluation we use the widths of the error ellipses, perpendicular to the direction of the course. Through the simulation of navigating a robot along the center lines of corridors the effectiveness of the proposed method is confirmed. ing landmarks the position estimation is updated in the same way. The behaviors of using two types of landmarks, a line type landmark and a point type one, are examined. The position estimation using a particular landmark is ex- pressed by an error ellipse which is derived from the error covariance update and which shows the directional error distribution of the estimated position error. Though it is favorable if the radius of the error ellipse is small in all di- rections, we think the width of the ellipse along the course is important and propose to use it as the criterion for the selection of the landmark. By the simulation of navigating a robot along the center lines of corridors the effectiveness of navigation based on the proposed landmark selection method is shown.

A Fuzzy Logic Based Robot Navigation System

Abstract: One of the key issues in mobile robot navigation is coping with uncertainty in a dynamic environment. One possible solutions lies in behaviors, but there is a problem with standard behavior arbitration techniques. To combat this problem, David Payton introduced a command arbitration net that minimizes the loss of information between behaviors. We have extended his approach using fuzzy logic. Some benefits of using fuzzy logic include simplicity, extensibility and understandability, especially in the area of sensor fusion.

Behavior-based mobile robot using active sensor fusion

Abstract: The authors present a navigation system using multiple sensors for unknown and dynamic indoor environments. To achieve robustness and flexibility in the mobile robot, a behavior-based system architecture is developed consisting of multilayered behaviors using multiple sensors that were ultrasonic sensors and a video camera. Basic behaviors required for navigation, such as avoiding obstacles, moving toward free space, and following targets are redundantly developed as agents and combined in a behavior-based system architecture. The capabilities of the system were demonstrated in unstructured real office environments using an indoor mobile robot. >