Showing papers on "Mobile robot navigation published in 1995"

Probabilistic robot navigation in partially observable environments

Abstract: Autonomous mobile robots need very reliable navigation capabilities in order to operate unattended for long periods of time. This paper reports on first results of a research program that uses par tially observable Markov models to robustly track a robots location in office environments and to direct its goal-oriented actions. The approach explicitly maintains a probability distribution over the possible locations of the robot taking into account various sources of uncertainly including approximate knowledge of the environment and actuator and sensor uncertainty. A novel feature of our approach is its integration of topological map information with approximate metric information. We demonstrate the robustness of this approach in controlling an actual indoor mobile robot navigating corridors.

A sensor-based navigation for a mobile robot using fuzzy logic and reinforcement learning

Abstract: The proposed navigator consists of an avoidance behavior and goal-seeking behavior. Two behaviors are independently designed at the design stage and then combined them by a behavior selector at the running stage. A behavior selector using a bistable switching function chooses a behavior at each action step so that the mobile robot can go for the goal position without colliding with obstacles. Fuzzy logic maps the input fuzzy sets representing the mobile robot's state space determined by sensor readings to the output fuzzy sets representing the mobile robot's action space. Fuzzy rule bases are built through the reinforcement learning which requires simple evaluation data rather than thousands of input-output training data. Since the fuzzy rules for each behavior are learned through a reinforcement learning method, the fuzzy rule bases can be easily constructed for more complex environments. In order to find the mobile robot's present state, ultrasonic sensors mounted at the mobile robot are used. The effectiveness of the proposed method is verified by a series of simulations. >

Navigation system for an automotive vehicle

Abstract: A navigation system for an automotive vehicle designed to display a road map image around the vehicle in correlation with the current position of the automotive vehicle. The navigation system is adapted to determine a best navigation route to a selected destination on the basis on the approximated time necessary to travel such a navigation route in correspondence to its travel length and speed rate.

Robot hand-eye coordination based on stereo vision

Abstract: This article describes the theory and implementation of a system that positions a robot manipulator using visual information from two cameras. The system simultaneously tracks the robot end-effector and visual features used to define goal positions. An error signal based on the visual distance between the end-effector and the target is defined, and a control law that moves the robot to drive this error to zero is derived. The control law has been integrated into a system that performs tracking and stereo control on a single processor with no special-purpose hardware at real-time rates. Experiments with the system have shown that the controller is so robust to calibration error that the cameras can be moved several centimeters and rotated several degrees while the system is running with no adverse effects. >

A complete navigation system for goal acquisition in unknown environments

Abstract: Most autonomous outdoor navigation systems tested on actual robots have centered on local navigation tasks such as avoiding obstacles or following roads. Global navigation has been limited to simple wandering, path tracking, straight-line goal seeking behaviors, or executing a sequence of scripted local behaviors. These capabilities are insufficient for unstructured and unknown environments, where replanning may be needed to account for new information discovered in every sensor image. To address these problems, the authors developed a complete system that integrates local and global navigation. The local system uses a scanning laser rangefinder to detect and avoid obstacles. The global system uses an incremental path planning algorithm to optimally replan the global path for each detected obstacle. A control arbiter steers the robot to achieve the proper balance between safety and goal acquisition. This system was tested on a real robot and successfully drove it 1.4 kilometers to find a goal given no a priori map of the environment.

A fuzzy logic based extension to Payton and Rosenblatt's command fusion method for mobile robot navigation

Abstract: Payton and Rosenblatt (1990) have proposed a command fusion method for combining outputs of multiple behaviors in a mobile robot navigation system such that information loss due to command fusion can be reduced. Using linguistic fuzzy rules to explicitly capture heuristics implicit in the Payton-Rosenblatt approach, we have extended their approach to a fuzzy logic architecture for mobile robot navigation in dynamic environments, which is simpler and easier to understand and modify. We have also developed and empirically tested a new defuzzification technique for alleviating difficulties in applying existing defuzzification methods to mobile robot navigation control. >

Travel control method, travel control device, and mobile robot for mobile robot systems

Abstract: In the travel control method in the mobile robot system including a plurality of mobile robots and the control station for controlling these mobile robot, the control station directs one of a plurality of mobile robots to the destination robot, responding to the direction, searches the route to the destination directed by the control station and sends the result to the control station. The control station which receives this in formation checks if the travel path searched by the mobile robot is already reserved by other mobile robots or not by the reservation table. If not, the control station informs the reserve completion to said mobile robot. The mobile robot which received the information of the reservation completion travels automatically along the travel path which is already reserved. In addition, said control station, when there are other mobile robots which disturb the travel of each mobile robot, directs the robot to wait or to take an alternate route according to the situation, or directs other mobile robots that disturb the travel to halt.

Map-based navigation for a mobile robot with omnidirectional image sensor COPIS

Abstract: We designed a new omnidirectional image sensor COPIS (Conic Projection Image Sensor) to guide the navigation of a mobile robot. The feature of COPIS is passive sensing of the omnidirectional image of the environment, in real-time (at the frame rate of a TV camera), using a conic mirror. COPIS is a suitable sensor for visual navigation in a real world environment. We report here a method for navigating a robot by detecting the azimuth of each object in the omnidirectional image. The azimuth is matched with the given environmental map. The robot can precisely estimate its own location and motion (the velocity of the robot) because COPIS observes a 360/spl deg/ view around the robot, even when all edges are not extracted correctly from the omnidirectional image. The robot can avoid colliding against unknown obstacles and estimate locations by detecting azimuth changes, while moving about in the environment. Under the assumption of the known motion of the robot, an environmental map of an indoor scene is generated by monitoring azimuth change in the image. >

Mobile robot control system

Abstract: A mobile robot control system with plural mobile robots each of which moves along a predetermined route in the same area. One mobile robot gives way to the other mobile robot when the mobile robot receives a signal emitted by the other mobile robot. A mobile robot moving on a predetermined route has a sensor which senses whether or not an obstacle exists on the route. The sensor senses again after a predetermined time from the first sensing whether the sensor still detects the obstacle existing on the route at the first sensing.

A complete navigation system for goal acquisition in unknown environments

Abstract: Most autonomous outdoor navigation systems tested on actual robots have centered on local navigation tasks such as avoiding obstacles or following roads. Global navigation has been limited to simple wandering, path tracking, straight-line goal seeking behaviors, or executing a sequence of scripted local behaviors. These capabilities are insufficient for unstructured and unknown environments, where replanning may be needed to account for new information discovered in every sensor image. To address these problems, we have developed a complete system that integrates local and global navigation. The local system uses a scanning laser rangefinder to detect obstacles and recommend steering commands to ensure robot safety. These obstacles are passed to the global system which stores them in a map of the environment. With each addition to the map, the global system uses an incremental path planning algorithm to optimally replan the global path and recommend steering commands to reach the goal. An arbiter combines the steering recommendations to achieve the proper balance between safety and goal acquisition. This system was tested on a real robot and successfully drove it 1.4 kilometers to find a goal given no a priori map of the environment.

Obstacle detection with omnidirectional image sensor HyperOmni Vision

Abstract: Described here is an image sensor with a hyperboloidal mirror for vision based navigation of a mobile robot. Its name is HyperOmni Vision. This sensing system can acquire an omnidirectional view around the robot, in real-time, with use of a hyperboloidal mirror. The authors show a prototype of a mobile robot system with HyperOmni Vision and a method for estimating the motion of the robot and finding unknown obstacles.

Reliable navigation using landmarks

Abstract: Building a truly reliable mobile robot system-one that can navigate without failures for long periods of time (weeks or months)-requires making clear assumptions bounding uncertainty and enforcing those assumptions by appropriately engineering the robot and its workspace. Weak assumptions may result in low-cost engineering but make the navigation problem intractable. On the other hand, strict assumptions may simplify navigation but reduce the flexibility of the resulting system. The work presented in this paper investigates the tradeoff between "computational complexity" and "physical complexity" and advocates landmarks as a way of managing this tradeoff. We first define a formal navigation problem which incorporates enough assumptions to make it computationally tractable. We then use landmarks to enforce those assumptions. By implementing this system on our mobile robot we show that the assumptions are enforceable, that the engineering costs of using landmarks are acceptable, and that the resulting navigation system is both efficient and robust.

Autonomous navigation system for a mobile robot or manipulator

Abstract: In an autonomous navigation system for a mobile robot or a manipulator which is intended to guide the robot through the workspace to a predetermined target point in spite of incomplete information without colliding with known or unknown obstacles. All operations are performed on the local navigation level in the robot coordinate system. In the course of this, occupied and unoccupied areas of the workspace are appropriately marked and detected obstacles are covered by safety zones. An intermediate target point is defined in an unoccupied area of the workspace and a virtual harmonic potential field is calculated, whose gradient is followed by the robot. Mobile robots with such an autonomous navigation system can be used as automated transport, cleaning and service systems.

Mobile robot navigation using the range-weighted Hough transform

Abstract: Accurate navigation of a mobile robot in cluttered rooms using a range-measuring laser as a sensor has been achieved. To extract the directions and distances to the walls of the room the range-weighted Hough transform is used. The following experimental results are emphasized: The robot extracts the walls of the surrounding room from the range measurements. The distances between parallel walls are estimated with a standard deviation smaller than 1 cm. It is possible to navigate the robot along any preselected trajectory in the room. One special case is navigation through an open door detected by the laser. The accuracy of the passage is 1 cm at a speed of 0.5 m/s. The trajectory is perpendicular to the wall within 0.5 degrees in angle. When navigating through corridors, the accuracy is better than 1 cm at 0.8 m/s-the maximum speed of the robot. Odometric data and laser measurements are combined using the extended Kalman filter. The size of the cluttered rectangular room and the position and orientation (pose) of the robot are estimated during motion. The extraction and the resulting navigation are very robust against both spurious measurements in the laser measurements and disturbing objects. >

Multi-robot cooperation through incremental plan-merging

Abstract: This paper presents an approach we have recently developed for multi-robot cooperation. It is based on a paradigm where robots incrementally merge their plans into a set of already coordinated plans. This is done through exchange of information about their current state and their future actions. This leads to a generic framework which can be applied to a variety of tasks and applications. The paradigm, called plan-merging paradigm, is presented and illustrated through its application to planning, execution and control of a large fleet of a autonomous mobile robots for load transport tasks in a structured environment.

On-line map building and navigation for autonomous mobile robots

Abstract: The problem of sensor-based robot motion planning in unknown environments is addressed. The proposed solution approach prescribes the repeated sequence of two fundamental processes: perception and navigation. In the former, the robot collects data from its sensors, builds local maps and integrates them with the global maps so far reconstructed, using fuzzy logic operators. During the navigation process, a planner based on the A* algorithm proposes a path from the current position to the goal. The robot moves along this path until one of two termination conditions is verified namely (i) an unexpected obstructing obstacle is detected, or (ii) the robot is leaving the area in which reliable information has been gathered. Experimental results are presented for a Nomad 200 mobile robot.

Motion planning for a steering-constrained robot through moderate obstacles

Abstract: Most mobile robots use steering mechanisms to guide their motion. Such mechanisms have stops that constrain the rate at which the robot can change its direction. We study a point robot in the plane subject to such constraints, in the presence of a class of obstacles we call moderate obstacles. We consider the case in which the robot has a reverse gear that allows it to back up, as well as the case when it does not, All our algorithms run in polynomial time and produce paths whose lengths are either optimal or within an additive constant of optimal.

A fuzzy system for indoor mobile robot navigation

Abstract: An autonomous mobile robot (AMR) has to cope with uncertain, incomplete or approximate information. Moreover it has to identify sudden perceptual situations to manoeuvre in real time. This paper describes a fuzzy rule based system (FRBS) approach controlling the movement of an autonomous mobile robot (MORIA). Difficult guiding and controlling properties of the robot are achieved by combining local actions and global strategies within the fuzzy controller. Different behaviors and perceptions are detected with the help of fuzzy rules and stored in fuzzy state variables (FSV). These state variables activate different fuzzy rule sets which in turn change the behavior of the fuzzy controller. >

Navigation system for an autonomous mobile robot

Abstract: A navigation system for an autonomous mobile robot within an environment which comprises coded signs at predetermined points comprising means for storing data regarding said environment, including data regarding the positions of said coded signs relative to the environment, passive vision systems for the image acquisition and automatic recognition of said coded signs, a computer for estimating its own position and orientation relative to one of said coded signs and to the environment, means for acquiring the location of target positions, means for planning a path to be covered within said environment to reach target positions, and means for controlling the robot motion based on the stored path data.

Route making system for a mobile robot

Abstract: A route making system calculates a route for a mobile robot based on input area information including an attribute of each area. The mobile robot travels along the calculated route and carries out work proper for the attribute of each area while traveling. A mobile robot control system controls traveling and work of a mobile robot based on input area information. The mobile robot carries out work proper for the attribute of each area.

Laying and sensing odor markings as a strategy for assisting mobile robot navigation tasks

Abstract: After observing the use of odor by insects for navigation and location, the authors have developed an odor marking and detection system for mobile robots. Such a system will provide the basis for investigating the use of odor markings as an aid to mobile robot navigation. >

Robot Navigation: Integrating Perception, Environmental Constraints and Task Execution Within a Probabilistic Framework

Abstract: This paper proposes an integrated approach to robot navigation that incorporates task-related information needs, perceptual capabilities, robot knowledge metrics and spatial characteristics of the environment into the motion planning process. Autonomous robots are modelled as discrete-time dynamic systems that implement optimal or suboptimal control policies in their choice of appropriate control actions. A stochastic lattice model, the Inference Grid, is used to represent spatially distributed information. Various information metrics are defined to measure the extent, accuracy and complexity of the robot's world model, and to quantify the information needs of a task. A dual control architecture allows the robot to servo on the information required to solve a given task, and employs multi-objective optimization methods to plan the robot's perceptual and motor actions in an integrated manner.

Mathematical Foundations of Navigation and Perception for an Autonomous Mobile Robot

Abstract: This paper concerns the application of techniques from estimation theory to the problem of navigation and perception for a mobile robot. After a brief introduction, a hierarchical architecture is presented for the design of a mobile robot navigation system. The control system for a mobile robot is found to decompose naturally into a set of layered control loops, where the layers are defined by the level of abstraction of the data, and the cycle time of the feed-back control. The levels that occur naturally are identified as the level of signal, device, behaviour, and task.

Method and apparatus for providing navigation guidance

Abstract: A method and apparatus (10) for providing navigation guidance via a land vehicle by providing a navigation route planner (24) having a road network database (12) for planning a navigation route along the road network, determining a current estimated position of the land vehicle, communicating maneuver instructions to a driver of the land vehicle at a predetermined maneuver distance base value before the land vehicle reaches a required maneuver along the planned navigation route, and detecting and quantifying current environmental travel conditions for assisting a navigation device in guiding the land vehicle along the planned navigation route.

Evolving non-Trivial Behaviors on Real Robots: an Autonomous Robot that Picks up Objects

Abstract: Recently, a new approach that involves a form of simulated evolution has been proposed for the building of autonomous robots However, it is still not clear if this approach may be adequate to face real life problems In this paper we will show how control systems that perform a non-trivial sequence of behaviors can be obtained with this methodology by carefully designing the conditions in which the evolutionary process operates In the experiment described in the paper, a mobile robot is trained to locate, recognize, and grasp a target object The controller of the robot has been evolved in simulation and then downloaded and tested on the real robot

A numerical technique for planning motion strategies of a mobile robot in presence of uncertainty

Abstract: This paper addresses the problem of planning the motions of a circular mobile robot moving amidst polygonal obstacles with uncertainty in robot control and sensing. The robot is equipped with sensors which, if properly used, may provide information to overcome the uncertainty accumulated during the motions. The position sensor is based on dead-reckoning, the error then results in a cumulative uncertainty. A proximity sensor may be used to localize the robot with respect to the obstacles of the environment. The robot can also gain information by entering inside landmark areas where the position error is assumed to be bounded. The authors describe a planner which produces robust motion strategies composed of sensor-based motion commands which guarantee that, given an explicit model of the error accumulated by the motion commands, the robot can reach safely its goal with an error lower than a pre-specified value. It is based on a propagation of a numerical potential and on a geometric analysis of the reachability of environmental features. This planner exhibits a set of powerful capabilities: while it allows motion primitives which accumulate uncertainty to be considered, it is able, whenever possible, to navigate without relocalizing the robot when the task does not impose it, and also to make a proper use of the sensors. Several examples run with the planner are presented.

Following a wall by an autonomous mobile robot with a sonar-ring

Abstract: Presents a robust method for an autonomous mobile robot with a sonar-ring to follow walls. The sonar-ring consists of multiple ultrasonic range sensors. The proposed wall-following algorithm makes a robot able to follow a wall in various shapes such as a square wall, a circular wall etc. The autonomous mobile robot "Yamabico" is used for experiments after being equipped with a 12 directional sonar-ring. The on-board controller of the robot decides its motion based on sonar-ring range data every 3 centimeters going forward. The authors carried out many experiments with this autonomous mobile robot, and investigated the validity and the limits of this method.