Showing papers on "Mobile robot navigation published in 1986"

Outdoor scene analysis using range data

Abstract: This paper describes techniques for outdoor scene analysis using range data. The purpose of these techniques is to build a 3-D representation of the environment of an mobile robot equipped with a range sensor. Algorithms are presented for scene segmentation, object detection, map building, and object recognition. We present results obtained in an outdoor navigation environment in which a laser range finder is mounted on a vehicle. These results have been successfully applied to the problem of path planning through obstacles.

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 mobility control. The purpose of this paper is to describe a new algorithm for omnidirectional 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.

Robot navigation algorithms using learned spatial graphs

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.

Multisensory robots and sensor-based path generation

Abstract: The paper first outlines the recent sensory developments in the DFVLR robotics lab, these are different force-torque sensors, laser range finders, inductive sensors and sensor balls for robot and 3D-computer-grafic control. With the example of our proposed multisensory arrangement implying vision, range sensing, force-torque and speech, the fine-motion planning and path generation techniques as developed in our lab are discussed. The special case of a two-arm cooperative robot using two force-torque-sensors is treated in more detail. Practical results are demonstrated in a film including cooperative two arm robot control.

Minimum-time navigation of an unmanned mobile robot in a 2-1/2D world with obstacles

Abstract: In a 2-1/D world an isolines-based world representation is employed. An algorithm of navigation is proposed based upon polygonization of the isolines, and use of the vertices of the polygon as nodes in the graph search. Quanitative recommendations are given concerning the required density of isolines and the error of polygonization. When a physical model of mechanical motion is applied, this algorithm of navigation provides minimum-time trajectories of motion. The results of navigation are illustrated using a simulation system developed for an Intelligent Mobile Autonomous System (unmanned robot).

Path Planning for a Vision-Based Autonomous Robot

Abstract: THE VISIONS RESEARCH ENVIRONMENT AT THE UNIVERSITY OF MASSACHUSETTS PRO- VIDES AN INTEGRATED SYSTEM FOR THE INTERPRETATION OF VISUAL DATA. TO PRO- VIDE A TESTBED FOR MANY OF THE ALGORITHMS DEVELOPED WITHIN THIS FRAMEWORK, A MOBILE ROBOT HAS BEEN ACQUIRED. THE TEST DOMAINS OF INTERACTIONS ARE TWOFOLD: THE INTERIOR OF A LARGE RESEARCH CENTER BUILDING (ROOMS, HALLS, FOYERS, DOORWAYS, ETC.) AND THE IMMEDIATE OUTDOOR AREA SURROUNDING THE BUILDING (SIDEWALKS, GRAVEL PATHS, GRASS PATHS, GRASS PATCHES, BUILDING ENTRANCES, ETC.). A MULTI-LEVEL REPRESENTATION AND THE ACCOMPANYING ARCHITECTURE USED TO SUPPORT MULTI-SENSOR NAVIGATION (PREDOMINANTLY VISUAL) ARE DESCRIBED. A HYBRID VERTEX-GRAPH FREE-SPACE REPRESENTATION BASED UPON THE DECOMPOSITION OF FREE SPACE INTO CONVEX REGIONS CAPABLE FOR USE IN BOTH INDOOR AND LIMIT- ED OUTDOOR NAVIGATION IS DISCUSSED. THIS "MEADOW MAP" IS PRODUCED VIA THE RECURSIVE DECOMPOSITION OF THE INITAL BOUNDING AREA OF TRAVERSABILITY AND ITS ASSOCIATED MODELLED OBSTACLES. OF PARTICULAR INTEREST IS THE CAPABIL- ITY TO HANDLE MULTIPLE TERRAIN TYPES (SIDEWALKS, GRASS, GRAVEL, ETC.). "TRANSITION ZONES" EASE THE PASSAGE OF THE ROBOT FROM ONE TERRAIN TYPE TO ANOTHER. A HIERARCHICAL PATH PLANNER, (MISSION PLANNER, NAVIGATOR, AND PILOT), THAT UTILIZES THE DATA AVAILABLE IN THE ABOVE REPRESENTATIONAL SCHEME IS

Robot navigation in an unexplored terrain

Abstract: Navigation planning is one of the most vital aspects of an autonomous mobile robot. Robot navigation for completely known terrain has been solved in many cases. Comparatively less research dealing with robot navigation in unexplored obstacle terrain has been reported in the literature. In recent times this problem has been addressed by adding learning capability to a robot. The robot explores terrain using sensors as it navigates, and builds a terrain model in an incremental manner. In this article we present concurrent algorithms for robot navigation in unexplored terrain. The performance of the concurrent algorithms is analyzed in terms of planning time, travel time, scanning time, and update time. The analysis reveals the need for an efficient data structure to store an obstacle terrain model in order to reduce traversal time, and also to incorporate learning. A modified adjacency list is proposed as a data structure for storing a spatial graph that represents an obstacle terrain. The time complexities of the algorithms that access, maintain, and update the spatial graph are estimated, and the effectiveness of the implementation is illustrated.

Design of a robot force/motion server

Abstract: The design and implementation of a distributed robot manipulator controller based on a parallel architecture is introduced in this paper. We consider the robot manipulator as a robot force and motion server (RFMS) to the robot system to execute force and motion commands issued by the robot coordinator. In the server, computation is distributed to a number of processors to achieve a system capable of executing computation expensive tasks. The use of "c" programming language for both the system programming and the user interface provides a convenient environment to control such a system.

Vision navigation system for free-roaming mobile robots

Abstract: A vision navigation system for a mobile robot 21. The mobile robot has a plurality of light beacons 3, 5, 7 mounted on it to identify its location to fixed overhead television cameras 1 having a predefined viewing area. Navigation commands are generated by finding present robot location and transmitting new coordinates via the beacons which are used both for communicating with a master station and to locate the mobile apparatus. There are a minimum of three navigation beacons which are arranged in a tnangular pattern to enable robot direction to be determined, even when some beacons are obstructed from view of overhead cameras. The television system uses a gray scale image and has a video bus that transmits the actual pixel value synchronized with a pixel clock.

A method of autonomous locomotion for mobile robots

Abstract: _A navigation method is presented which enables a mobile robot to perform autonomous locomotion. The feasibility of this method was demonstrated using experimental hardware_a prototype robot with ultrasonic sensors. This method uses objects of simple shape, such as poles and flat surfaces of walls selected from the environment, as landmarks and a map which indicates the relations of these landmarks. The robot moves from a given point to another along a designated path using its sensors. At each point it measures the positions of the objects selected as landmarks and corrects its path. The following basic problems encountered in realizing this method are discussed: (a) path design connecting two points in the environment; (b) the control ofthe robot's path; (c) measurement ofthe objects' positions using an ultrasonic sensor; and (d) correction of error from the designated path. To navigate a mobile robot it is necessary to be able to control it so that a specified path is followed accurately. Since absolut...

Concurrent algorithms for autonomous robot navigation in an unexplored terrain

Abstract: Navigation planning is one of the most vital aspects of an autonomous mobile robot. The problem of navigation in a completely known obstacle terrain is solved in many cases. Comparatively less number of research results are reported in literature about robot navigation in a completely unknown obstacle terrain. In recent times, this problem is solved by imparting the learning capability to the robot. The robot explores the obstacles terrain using sensors and incrementally builds the terrain model. As the robot keeps navigating, the terrain model becomes more learned and the usage of sensors is reduced. The navigation paths are computed by making use of the existing terrain model. The navigation paths gradually approach global optimality as the learning proceeds. In this paper, we present concurrent algorithms for an autonomous robot navigation in an unexplored terrain. These concurrent algorithms are proven to be free from deadlocks and starvation. The performance of the concurrent algorithms is analyzed in terms of the planning time, travel time, scanning time, and update time. The analysis reveals the need for an efficient data structure for the obstacle terrain in order to reduce the navigation time of the robot, and also to incorporate learning. The modified adjacency list is proposed as a data structure for the spatial graph that represents the obstacle terrain. The time complexities of various algorithms that access, maintain, and update the spatial graph are estimated, and the effectiveness of the the implementation is illustrated.

Gravity-model errors in mobile inertial-navigation systems

Abstract: A high-accuracy inertial-navigation system (INS) is to be used to navigate a land-mobile Vehicle travelling at about 30 knots, Over time periods of 2-4 h or less. Important sources of navigation error are the errors in modeling the anomalous gravity forces acting on the vehicle. To obtain acceptable performance, the INS must be accurately compensated in real time for the anomalous gravity. A significant reduction in the growth of navigation errors can be obtained by stopping the vehicle periodically and processing zero-velocity updates in an on-board navigation filter. The land-navigation system design considerations that affect the growth of navigation error due to the gravity-model errors are examined here. These include the grid-spacing of the data base used to derive the real-time gravity compensation, the use of odometer and zero-sideslip measurement data for in-transit INS updating, and the frequency and accuracy of the at-rest zero-velocity updates which are the key to high-accuracy land navigation.

Omnidirectional Dynamic Vision Positioning For A Mobile Robot

Abstract: This paper presents a new positioning technique, called omnidirectional dynamic vision positioning, for use in navigating a mobile robot. A fisheye lens image system is used as an omnidirectional vision device. A positioning algorithm used with reference beacons determines the position of the robot in terms of a global positioning coordinate system. An accuracy analysis was conducted, and positioning errors were characterized. The experimental results verify the practicability and realizability of the new technique. The advantage of omnidirectional vision for navigation is the simplicity of recording an entire 2 tt radian scene without camera scanning.

A navigation algorithm for an intelligent vehicle with a laser rangefinder

Abstract: This paper describes a navigation algorithm for a vehicle equipped with a laser rangefinder sensor. The navigation algorithm is broken up into four parts, region classification, path planning, path smoothing, and path execution. Algorithms for region classification, path planning and path smoothing are presented. The navigation system was tested, and shown to produce fast, reliable results, in areas containing a high percentage of obstacles.

Robot navigation in unknown terrains of convex polygonal obstacles using learned visibility graphs

Abstract: The problem of navigating an autonomous mobile robot through an unexplored terrain of obstacles is the focus of this paper. The case when the obstacles are 'known' has been extensively studied in literature. The process of robot navigation in completely unexplored terrains involves both learning the information about the obstacle terrain and path planning. We present an algorithm to navigate a point robot in an unexplored terrain that is arbitrarily populated with disjoint convex polygonal obstacles in the plane. The navigation process is constituted by a number of traversals; each traversal is from an arbitrary source point to an arbitrary destination point. Initially, the terrain is explored using a sensor and the paths of traversal made may be sub-optimal. The visibility graph that models the obstacle terrain is incrementally constructed by integrating the information about the paths traversed so far. At any stage of learning, the partially learnt terrain model is represented as a learned visibility graph, and it is updated after each traversal. The proposed algorithm is proven to yield a convergent solution to each path of traversal. It is also shown that the learned visibility graph converges to the visibility graph with probability one, when the source and destination points are chosen randomly. Ultimately, the availability of the complete visibility graph enables the robot to plan globally optimal paths, and also obviates the further usage of sensors.

Adaptive Navigation of Automated Vehicles by Image Analysis Techniques

Abstract: Image analysis techniques are applied to adaptive automatic vehicle navigation. The proposed image-based navigation system is made adaptive to follow any selected path embedded in a curve-type path network. This is achieved with three major capabilities of the proposed system: path network learning, reference path setup, and guided path navigation. The first capability enables the system to extract relevant information out of a given network map, and the second collects along-path reference data for a selected path from the extracted network information. During guided path navigation, consecutive path images are taken by a television camera on the vehicle and then analyzed for navigation control along path curves and for angular turning at path crossings. The control structure of the automatic navigation process is modelled as a Moore-type sequential machine in automata theory. Correct path navigation is ascertained by verifying each path crossing encountered on the road against the reference data by an image matching technique. Simulation of vehicle movement with a computer-controlled pantilt is also described. Simulation results show the feasibility of the proposed approach.

Autonomous Mobile Robots.

Abstract: : Since 1981 the Mobile Robot laboratory of the Robotics Institute of Carnegie-mellon University has conducted basic research in areas crucial for autonomous robots. We have built three mobile robots as testbeds for new concepts in control, vision, planning, locomotion and manipulation. This report recounts our work in 1985. Included are two papers describing two-dimensional sonar mapping and navigation, and a proposal for a three dimensional sonar. Three papers cover recent results in stereo visual navigation - we have achieved a tenfold speedup and a tenfold increase in navigational accuracy over our first generation system, and have a much deeper understanding of some of the mathematical foundations. Three papers describe results in a road navigation task - we are now able to navigate a simple road network at walking speeds with a single color camera on a roving robot using a variety of image processing and navigation methods. Three papers describe aspects of motion control, motors, wheeled kinematics and vehicle dynamics. Two papers present our newest robots, Neptune and Uranus. A final article gives some along term motivations and expectations for mobile robot research, and the report ends with a bibliography of our publications. (Author)

Navigation and world modelling for a mobile robot: a progress report

Abstract: Factory robots function in highly engineered environments and thus can be made to function with very limited sensing and intelligence. The introduction of robots into such unconstrained environments such as a construction site or a mine requires a radically different approach. Such systems must sense and model their environment and base their actions on such a model. They must also apply intelligence so that they do not simply repeat actions, but accomplish goals.

Land navigation Demonstration Vehicle with a color map display for tactical use

Abstract: A Land navigation Demonstration Vehicle (LDV) has been assembled which fully automates the navigation task and provides the operator with a color map display derived from Digital Terrain Elevation Data (DTED). The system relieves the operator of the burdens associated with the tactical use of paper maps by providing accurate 3-dimensional position information using a strapdown inertial navigation platform aided by the Sandia Inertial Terrain Aided Navigation algorithm (SITAN). The map display and navigation instruments consist of a multi-processor SANDia Aerospace Computer (SANDAC) and a commercial Image Processing System (IPS). These interactive devices allow real-time map annotation and corrections of vehicle position errors. 7 refs., 9 figs., 1 tab.