Showing papers on "Mobile robot navigation published in 1985"

Position referencing and consistent world modeling for mobile robots

Abstract: In order to understand its environment, a mobile robot should be able to model consistently this environment, and to locate itself correctly. One major difficulty to be solved is the inaccuracies introduced by the sensors. The approach proposed in this paper to cope with this problem relies on 1) defining general principles to deal with uncertainties : the use of a multisensory system, favo ring of the data collected by the more accurate sensor in a given situation, averaging of different but consistent measurements of the same entity weighted with their associated uncertainties, and 2) a methodology enabling a mobile robot to define its own reference landmarks while exploring its environment. These ideas are presented together with an example of their application on the mobile robot HILARE.

Navigation for an intelligent mobile robot

Abstract: A navigation system is described for a mobile robot equipped with a rotating ultrasonic range sensor. This navigation system is based on a dynamically maintained model of the local environment, called the composite local model. The composite local model integrates information from the rotating range sensor, the robot's touch sensor, and a pre-learned global model as the robot moves through its environment. Techniques are described for constructing a line segment description of the most recent sensor scan (the sensor model), and for integrating such descriptions to build up a model of the immediate environment (the composite local model). The estimated position of the robot is corrected by the difference in position between observed sensor signals and the corresponding symbols in the composite local model. A learning technique is described in which the robot develops a global model and a network of places. The network of places is used in global path planning, while the segments are recalled from the global model to assist in local path execution. This system is useful for navigation in a finite, pre-learned domain such as a house, office, or factory.

Visual map making for a mobile robot

Abstract: Mobile robots sense their environment and receive error laden readings. They try to move a certain distance and direction, and do so only approximately. Rather than try to engineer these problems away it may be possible, and may be necessary, to develop map making and navigation algorithms which explicitly represent these uncertainties, but still provide robust performance. The key idea is to use a relational map, which is rubbery and stretchy, rather than try to place observations in a 2-d coordinate system.

Dynamic world modeling for an intelligent mobile robot using a rotating ultra-sonic ranging device

Abstract: A system which performs task-oriented navigation for an intelligent mobile robot is described in this paper. This navigation system is based on a dynamically maintained model of the local environment, called the "Composite Local Model." The Composite Local Model integrates information from a rotating sonar sensor, the robot's touch sensor and a pre-learned Global Model as the robot moves through its environment. Techniques are described for constructing a line segment description of the most recent sensor scan (the Sensor Model), and for integrating such descriptions to build up a model of the immediate environment (the Composite Local Model). Model integration is based on a process of reinforcing the confidence in consistent information while decaying the confidence in inconsistent information. The estimated position of the robot is corrected by the difference in position between observed sensor signals and the corresponding symbols in the Composite Local Model. This system is useful for navigation in a finite, pre-learned domain such as a house, office, or factory.

Some Heuristics for the Navigation of a Robot

Abstract: A mobile robot is required to navigate around barriers in an unexplored environment. Some heuristic strategies to aid such navigation are discussed here. Being heuristic, these methods can be neither exhaustively tested nor proved effec tive in all cases. However, examples are given to demonstrate their usefulness in obstacle avoidance. In a simple case of sufficient generality, the heuristics are shown to be effective.

A spatial representation system for mobile robots

Abstract: A two dimensional spatial representation system is presented which makes efficient use of distance information for accomplishing common mobile robot tasks. Ways to use the representation for route planning, positioning, and execution monitoring are presented. The representation is very space efficient, and all the transformations to be performed on it are computationally tractable.

Redundant Sensors for Mobile Robot Navigation

Abstract: : Redundant sensors are needed on a mobile robot so that the accuracy with which it perceives its surroundings can be increased. Sonar and infrared sensors are used here in tandem, each compensating for deficiencies in the other. The robot combines the data from both sensors to build a representation which is more accurate than if either sensor were used alone. Another representation, the curvature primal sketch, is extracted from this perceived workspace and is used as the input to two path planning programs: one based on configuration space and one based on a generalized cone formulation of free space. (Author).

Visual navigation system for mobile robots

Abstract: A visual navigation system navigates an electrically controllable apparatus such as a mobile robot. Navigation commands are generated to move the mobile apparatus based upon the location of the mobile apparatus. Once the location of the mobile apparatus is determined and the coordinates of a new position are provided, then the commands are transmitted to the mobile apparatus to relocate to the new position. The repetitive update of the location and move commands ensure the movement of the mobile apparatus without wire or rails.

Learned Navigation Paths for a Robot in Unexplored Terrain.

Abstract: Finding optimal paths for robot navigation in known terrain has been studied for some time but, in many important situations, a robot would be required to navigate in completely new or partially explored terrain. We propose a method of robot navigation which requires no pre-learned model, makes maximal use of available information, records and synthesizes information from multiple journeys, and contains concepts of learning that allow for continuous transition from local to global path optimality. The model of the terrain consists of a spatial graph and a Voronoi diagram. Using acquired sensor data, polygonal boundaries containing perceived obstacles shrink to approximate the actual obstacles surfaces, free space for transit is correspondingly enlarged, and additional nodes and edges are recorded based on path intersections and stop points. Navigation planning is gradually accelerated with experience since improved global map information minimizes the need for further sensor data acquisition. Our method currently assumes obstacle locations are unchanging navigation can be successfully conducted using two-dimensional projections, and sensor information is precise.

Dynamic scene analysis for a mobile robot in a man-made environment

Abstract: Analysis of scene viewed continuously from a robot moving in a man-made environment, such as a building or a plant, yields useful information for the navigation. The knowledge on the environment, richness of the scene in vertical edges and the flatness of the floor, is arranged in constraints for the dynamic scene analysis. The rotational component of camera motion is estimated first from image points invarient from translation. After compensating for movements by the rotation between the consecutive images, the foci of expansion of translational motion of both the robot and moving objects are determined.

Dynamic Omnidirectional Vision For Mobile Robots

Abstract: Mobile robotic devices hold great promise for a variety of applications in industry. A key step in the design of a mobile robot is to determine the navigation method for the mobility control. The purpose of this paper is to describe a new algorithm for omnidirec-tional vision navigation. A prototype omnidirectional vision system and the implementation of the navigation techniques using this modern sensor and an advanced automatic image processor is described. The significance of this work is in the development of a new and novel approach - dynamic omnidirectional vision for mobile robots and autonomous guided vehicles.

Visual algorithms for autonomous navigation

Abstract: The Computer Vision Laboratory at the University of Maryland is designing and developing a vision system for autonomous ground navigation. Our approach to visual navigation segments the task into three levels called long range, intermediate range and short range navigation. At the long range, one would first generate a plan for the day's outing, identifying the starting location, the goal, and a low resolution path for moving from the start to the goal. From time to time, during the course of the outing, one may want to establish his position with respect to the long range plan. This could be accomplished by visually identifying landmarks of known location, and then triangulating to determine current position. We describe a vision system for position determination that we have developed as part of this project. At the intermediate range, one would look ahead to determine generally safe directions of travel called corridors of free space. Short range navigation is the process that, based on a detailed topographic analysis of one's immediate environment, enables us to safely navigate around obstacles in the current corridor of free space along a track of safe passage. We describe a quadtree based path planning algorithm which could serve as the basis for identifying such tracks of safe passage.

Method and apparatus for filtering reflections from direct images for mobile robot navigation

Abstract: A visual navigation system that rejects reflected images navigates an electrical controllable apparatus such as a mobile robot. The mobile robot is fitted with a minimum of three navigation beacons which emit a light visible to overhead television cameras. The beacons area arranged so as to form a triangle. The shape and the dimension of the triangular pattern are measured and stored in a memory unit within the visual navigation system, and when a reflected image is received it will be characterized by a different angle and thus the vision navigation system is able to distinguish the reflected image from the primary image of the mobile robot.

Navigation system and method

Abstract: A mobile receiver determines its position from received hyperbolic terrestrial navigation system signals (e.g. Loran-C) and geostationary earth satellite signals, the latter being spectrum spread with a chipping code time locked to a standard such as the Loran-C signals, by time comparing the chipping code with the Loran-C signals. in the case of two Loran-C transmitters and one satellite the mobile receiver determines one line of position from the time comparison and another line of position from the received Loran-C signals assumption being made to the effect that the receiver is on the earth's surface. Integrating a terrestrial navigation system e.g. Loran-C with satellite signals in this manner effectively enhances the range of Loran-C without requiring high peak power pulses from the satellite.

Use Of Landmarks For Mobile Robot Navigation

Abstract: The ideas that follow in this paper relate to the central theme of autonomous mobile robot navigation. Particular attention is given to the issue of designing a capability of landmark recognition. The proposed scheme of landmark recognition is intended to correct for the problem of discrepancies between the robot's actual location and the robot's estimate of its location. Acknowledgements: My graditude is extended to Tom Mowbray and John Bradstreet for their helpful discussions of this report topic. Keywords: Mobile robot navigation, robot vision, dynamic modeling.

A Decision System For Autonomous Robot Navigation Over Rough Terrain

Abstract: In the implementation of an autonomous mobile robot, the navigation system must be able find an acceptable path through a region of multi-valued traversal costs (as opposed to a binary regime of obstacle avoidance). Information must be efficiently represented, with sufficient information density in the robot's immediate navigation domain, in a manner which facilitates a process of learning the terrain. This paper discusses a decision system built around a "Routing-Engine" employing a cellular-array processor to propagate a wave over an two-dimensional map in which the pointwise traversal costs are represented as pointwise refractive indices. The path returned is the locus of local normals to the wavefront of the first wave, originating at the robot's current location, to reach the goal. This routing-engine is run recursively on a hierarchical stack of maps arranged in linear-spatial registration with the coarsest information resolution in the most global map. The central fovea of each map in the hierarchy is "blown-up" to yield a map more local to the vehicle, with the lowest level map possessing sufficient resolution to maneuver the robot. As the robot moves, its registration in the centre of each map in the stack is maintained by "scrolling" the maps over each other. As this is done, sensed information is propagated through the stack updating the information stored at each level. The system has been implemented successfully in simulation.

A novel approach to automotive navigation and map display. nav 85 - land navigation and location for mobile applications - papers presented at the 1985 conference of the royal institute of navigation, york, 9-11 september 1985

Abstract: A novel approach to automotive navigation and map display is described. In order for a navigation and display system to be both cost-effective and useful in automobiles, solutions are needed to problems in navigation, map data base, data storage, and display. A self-contained navigation technique is used, utilizing a compass and wheel sensors, a digital map data base, and an adaptive self-calibrating navigation algorithm. A prioritized map data base structure and a rugged digital tape deck solve problems of map data storage and distribution. Finally, a vector graphics cathode ray tube (crt) enables a flexible, high-resolution yet low-cost display to be implemented. A functional description of the etak navigator is presented along with a description of its basic hardware and software components. Alternate approaches and future applications are summarized. (Author/TRRL)

HERMIES-I: a mobile robot for navigation and manipulation experiments

Abstract: The purpose of this paper is to report the current status of investigations ongoing at the Center for Engineering Systems Advanced Research (CESAR) in the areas of navigation and manipulation in unstructured environments. The HERMIES-I mobile robot, a prototype of a series which contains many of the major features needed for remote work in hazardous environments is discussed. Initial experimental work at CESAR has begun in the area of navigation. It briefly reviews some of the ongoing research in autonomous navigation and describes initial research with HERMIES-I and associated graphic simulation. Since the HERMIES robots will generally be composed of a variety of asynchronously controlled hardware components (such as manipulator arms, digital image sensors, sonars, etc.) it seems appropriate to consider future development of the HERMIES brain as a hypercube ensemble machine with concurrent computation and associated message passing. The basic properties of such a hypercube architecture are presented. Decision-making under uncertainty eventually permeates all of our work. Following a survey of existing analytical approaches, it was decided that a stronger theoretical basis is required. As such, this paper presents the framework for a recently developed hybrid uncertainty theory. 21 refs., 2 figs.

An intelligent robot vision system for research applications

Abstract: This paper presents a Lisp-based robot vision system designed for research. It combines a Puma 560 robot arm, the computing power of a VAX 11/780 and a Grinnell Systems 275, the facility for artificial intelligence through Lisp, and sensing capability through a wrist-mounted camera. A description of the robot vision system includes system and software structure, the Lisp primitives for robot control, two vision algorithms, and a frame-based motion planner written in Lisp.

Robot languages in the eighties

Abstract: The scenario of general-purpose programming systems is rapidly changing; what are the consequences for robot programming? The programming environments built around ADA, UNIX, and Interlisp are useful for robot programming? After introducing the peculiar aspects of robot programming we will discuss some examples of general-purpose languages applied to robots and languages specifically designed for robotics. Criteria for making a choice between the two approaches should take into account the present state of the art. The need of a strong integration between different components as robots, vision systems, and other automation equipment could support the first approach. The solution of robot and robot users problems has, until now, supported the second approach, as indicated by the choices of European robot manufacturers. Anyway the expression of actions taken by different intelligent agents, as robots can be defined in the future, will require absolutely new linguistic media. We hope that robot programming in the eighties can develop experiences useful for the assessment in the field.

A Mobile Robot Project

Abstract: We are building a mobile robot which will roam around the AI lab observing and later perhaps doing. Our approach to building the robot and its controlling software differs from that used in many other projects in.a number of ways. (1) We model the world as three dimensional rather than two. (2) We build no special environment for our robot and insist that it must operate in the same real world that we inhabit. (3) In order to adequately deal with uncertainty of perception and control we build relational maps rather than maps embedded in a coordinate system, and we maintain explicit models of all uncertainties. (4) We explicitly monitor the computational performance of the components *of the control system, in order to refine the design of a real time control system for mobile robots based on a special purpose distributed computation engine. (5) We use vision as our primary sense and relegate acoustic sensors to local obstacle detection. (6) We use a new architecture for an intelligent system designed to provide integration of many early vision processes, and robust real-time performance even in cases of sensory overload, failure of certain early vision processes to deliver much information in particular situations, and computation module failure. A. I. Laboratory Working Papers are produced for internal circulation, and may contain information that is, for example, too preliminary or too detailed for formal publication. It is not intended that they should be considered papers to which reference can be made in the literature.

A novel approach to automotive navigation and map display

Abstract: In this paper, a novel approach to automotive navigation and map display is described. A self-contained navigation technique is used utilizing a compass and wheel sensors, a digital map data base, and an adaptive self- calibrating navigation algorithm. A functional description of the Etak Navigator is presented along with a description of its basic hardware and software components. Alternate approaches and future applications are summarized.

Experiments and thoughts on visual navigation

Abstract: We describe a second generation system that drives a camera-equipped mobile robot through obstacle courses. The system, which evolved from earlier work by Moravec [6], incorporates a new path planner and has supported experiments with interest operators, motion estimation algorithms, search constraints, and speed-up methods. In this paper we concentrate on the effects of constraint and on speed improvement. We also indicate some of our plans for a follow-on system.

Robot Vision Overview

Abstract: The field of robot vision is growing rapidly and promises to provide a great improvement in the versatility of industrial robots. The purpose of this paper is to review several techniques commonly used in robot vision applications, describe some of the solved problems, and to present examples of the various applications of these robot vision techniques. A basic premise of this paper is that the gap between C AD and C AM can be decreased using automatic inspection techniques. The robot vision applications are expanding at an unprecedented rate. This paper is a review and an attempt to tie together the diverse technologies available. The application of robot vision in the integrated manufacturing process may be vital to improvements in productivity and product quality.