Showing papers on "Mobile robot navigation published in 1994"

Optimal and efficient path planning for partially-known environments

Abstract: The task of planning trajectories for a mobile robot has received considerable attention in the research literature. Most of the work assumes the robot has a complete and accurate model of its environment before it begins to move; less attention has been paid to the problem of partially known environments. This situation occurs for an exploratory robot or one that must move to a goal location without the benefit of a floorplan or terrain map. Existing approaches plan an initial path based on known information and then modify the plan locally or replan the entire path as the robot discovers obstacles with its sensors, sacrificing optimality or computational efficiency respectively. This paper introduces a new algorithm, D*, capable of planning paths in unknown, partially known, and changing environments in an efficient, optimal, and complete manner. >

Path planning and guidance techniques for an autonomous mobile cleaning robot

Abstract: In the past mobile robot research was often focused on various kinds of point-to-point transportation tasks. Mobile robot application in service tasks, however, requires quite different path planning and guidance approaches. This paper introduces and discusses in detail specific planning and guidance techniques for a mobile floor-cleaning robot. A kinematic and geometric model of the robot and the cleaning units as well as a 2D-map of the indoor environment are used for planning an appropriate cleaning path. The path is represented by a concatenation of two kinds of typical motion patterns. Each pattern is defined by a sequence of discrete cartesian intermediate goal frames. These frames represent position and orientation of the vehicle and must be translated into motion commands for the robot. The steps of this semi-automatic path planning system are illustrated by a typical cleaning environment. Vehicle guidance includes execution of the planned motion commands, estimation of the robot location, path tracking, as well as detection of and reaction to (isolated) obstacles. For location estimation a least-squares fitting of corresponding geometric contours from the 2D-environment map and geometric 2D-sensor data is used. Obstacle detection is accomplished by testing geometric 2D-sensor data to be part of the preplanned cleaning path. Path planning and parts of the developed vehicle guidance system have been tested with the experimental mobile robot MACROBE. Results reported in this paper demonstrate the efficiency of the described planning, location estimation and path tracking procedures in basic floor-cleaning tasks. >

Using genetic algorithms to learn reactive control parameters for autonomous robotic navigation

Abstract: This article explores the application of genetic algorithms to the learning of local robot navigation behaviors for reactive control systems. Our approach evolves reactive control systems in variou...

Planning the motions of a mobile robot in a sensory uncertainty field

Abstract: Failures in mobile robot navigation are often caused by errors in localizing the robot relative to its environment This paper explores the idea that these errors can be considerably reduced by planning paths taking the robot through positions where pertinent features of the environment can be sensed It introduces the notion of a "sensory uncertainty field" (SUF) For every possible robot configuration q, this field estimates the distribution of possible errors in the robot configuration that would be computed by a localization function matching the data given by the sensors against an environment model, if the robot was at q A planner is proposed which uses a precomputed SUF to generate paths that minimize expected errors or any other criterion combining, say, path length and errors This paper describes in detail the computation of a specific SUF for a mobile robot equipped with a classical line-striping camera/laser range sensor It presents an implemented SUF-based motion planner for this robot and shows paths generated by this planner Navigation experiments were conducted with mobile robots using paths generated by the SUF-based planner and other paths The former paths were tracked with greater precision than the others The final section of the paper discusses additional research issues related to SUF-based planning >

Mobile robot obstacle avoidance in a computerized travel aid for the blind

Abstract: A blind traveler walking through an unfamiliar environment and a mobile robot navigating through a cluttered environment have an important feature in common: both have the kinematic ability to perform the motion, but are depended on a sensory system to detect and avoid obstacles. This paper describes the use of a mobile robot obstacle avoidance system as a guidance device for blind and visually impaired people. Just like electronic signals are sent to a mobile robot's motor controllers, auditory signals can guide the blind traveler around obstacles, or alternatively, they can provide an "acoustic image" of the surroundings. The concept has been implemented and tested in a new traveling aid for the blind, called the Navbelt. Experimental results of subjects traveling with the Navbelt in different surroundings are presented. >

Temporal coordination of perceptual algorithms for mobile robot navigation

Abstract: A methodology for integrating multiple perceptual algorithms within a reactive robotic control system is presented A model using finite state accepters is developed as a means for expressing perceptual processing over space and time in the context of a particular motor behavior This model can be utilized for a wide range of perceptual sequencing problems The feasibility of this method is demonstrated in two separate implementations The first is in the context of mobile robot docking where the mobile robot uses four different vision and ultrasonic algorithms to position itself relative to a docking workstation over a long-range course The second uses vision, IR beacon, and ultrasonic algorithms to park the robot next to a desired plastic pole randomly placed within an arena >

Map building for a mobile robot equipped with a 2D laser rangefinder

Abstract: This paper describes a method of building a map of the environment for a mobile robot equipped with a radial laser scanner. This sensor radially scans in a plane parallel to the ground providing a two-dimensional description of the environment. From this information, the map builder produces a set of (typically) short line segments which approximate the shape of almost any kind of environment (local map). As the robot moves, the different local maps obtained are integrated into a global map, representing, thus, the whole environment observed by the robot during its navigation. In particular the authors focus their attention on the update process of the global map. The proposed algorithm introduces what the authors call a "viewing sector" as a simple mechanism to reduce the number of local map segments to be checked for correspondence for each particular segment from the global map. A line segment fragmentation process is also used in order to manage partial correspondence between segments from both maps. The authors present experimental results obtained with this system that demonstrate successful map building. >

The localization problem for mobile robots

Abstract: A fundamental task for an autonomous mobile robot is that of localization-determining its location in a known environment. This problem arises in settings that range from the computer analysis of aerial photographs to the design of autonomous Mars rovers. L. Guibas et al. ((1992) have given geometric algorithms for the problem of enumerating locations for a robot consistent with a given view of the environment. We provide an on-line algorithm for a robot to move within its environment so as to uniquely determine its location. The algorithm improves asymptotically on strategies based purely on the "spiral search" technique of R. Baeza-Yates et al. (1993); an interesting feature of our approach is the way in which the robot is able to identify "critical directions" in the environment which allow it to perform late stages of the search more efficiently. >

On-line vehicle and pedestrian detections based on sign pattern

Abstract: Real time detection methods of moving vehicles and pedestrians for navigation of the mobile robot are proposed. The method is based on a locomotion strategy, viz. signature-based stereotype motion. Signature of the moving vehicle is the shadow underneath the vehicle which is darker than any other parts of the asphalt paved road. Signature of the pedestrian is rhythm of walking. Rhythm of walking is unique to the pedestrian, and not influenced by time, weather, sunlight, shadow, and distance. Moreover, it is independent from clothes the pedestrian puts on. The result of experiments verify the validity of the methods. >

Mobile robot localization using landmarks

Abstract: We describe an efficient algorithm for localizing a mobile robot in an environment with landmarks. We assume that the robot has a camera and maybe other sensors that enable it to both identify landmarks and measure the angles subtended by these landmarks. We show how to estimate the robot's position using a new technique that involves a complex number representation of the landmarks. Our algorithm runs in time linear in the number of landmarks. We present results of our simulations and propose how to use our method for robot navigation. >

Robot navigation from a Gibsonian viewpoint

Abstract: Gibson's insights into how optic flow can be used by animals to guide their actions have been formalized to some extent in Warren's laws of control. We noted that these laws are applicable to any moving agent, thus this approach could be very successful in the domain of behavior-based robotics. To demonstrate this we devised control laws for the obstacle avoidance problem in mobile robotics. Two laws of control relevant to the problem were proposed and tested on an actual robot in an unmodified office environment. The success and occasional, yet understandable, failures of these two laws show that the Gibsonian approach to visually guided navigation is very promising. >

Sensing odour trails for mobile robot navigation

Abstract: By monitoring or following trails layed on the ground a mobile robot can perform several useful navigation tasks. An example would be following a trail layed on an outward journey in order to later find the way back to the starting point. This paper describes the latest stage in the development of a robot navigation system based on laying down and detecting trails of volatile chemicals. Previously a prototype olfactory sensor was developed which showed the feasibility of having a mobile robot follow an odour trail on the floor. This prototype sensor has now been improved by managing airflow in the vicinity of the sensor. This has decreased the sensor response time and improved rejection of spurious odour signals carried by airflow in the room. A simple and effective applicator has also been developed for laying odour trails. >

Imagination and situated cognition

Abstract: We describe a novel agent architecture based on the idea that cognition is imagined interaction, i.e. that cognitive tasks are performed by interacting with an imaginary world. We demonstrate the architecture by its application to a subsumption-based mobile robot. The robot's interactive abilities include exploration of an environment and goal-directed navigation within a previously explored environment. Imagination enables the robot to read and make use of maps, allowing it to reason about unfamiliar environments as well.

Recent Trends in Mobile Robots

Abstract: The book is a collection of the most recent works in mobile robots. The contributing authors are experts in the area and are from all over the world, including Australia, Canada, France, Italy, Japan, Spain, Norway and the US. These experts report on advanced technologies as well as fundamental issues. From the book, readers will be able to see the recent trends in mobile robots from an international perspective. The following topics are covered: motion planning of mobile robots in unknown environments; environment modelling using advanced sensing technologies; dynamic mobile robot navigation; non-linear control of mobile robots; computation environments for mobile robots; coordination between mobility and manipulability; and advanced applications of mobile robots.

Odor sensing for robot guidance

Abstract: There is no generally applicable technique for finding the position of an autonomous mobile robot operating in an un structured or varying environment. This article describes a project to investigate the use of short-lived navigational mark ers consisting of olfactory chemicals to guide mobile robots and to help them search and explore efficiently. Such a method of laying a trail to mark the path of a robot provides differ ential navigational information relative to the starting point and starting direction. Many insects employ olfactory cues as navigation aids and to improve their efficiency when searching for food. Three scenarios are proposed in which navigational markers can be of assistance to a mobile robot. The design and characteristics of an adsorbed mass olfactory sensor are described. This sensor was designed to be mounted on a mo bile robot and is suitable for detecting and tracking olfactory chemicals. The performance of this sensor is described together with preliminary results of using it t...

A self-organizing representation of sensor space for mobile robot navigation

Abstract: The paper describes a sensor based navigation scheme which makes use of a global representation of the environment by means of a self-organizing map or Kohonen network. In contrast to existing methods for self-organizing environment representation, this discrete map is not represented in the world domain or in the configuration space of the vehicle, but in the sensor domain. The map is built by exploration. A conventional path planning technique now gives a path from current state to a desired state in the sensor domain, which can be followed using sensor based control. Collisions with obstacles are detected and used in the path planning. Results from a simulation show that the learned representation gives correct paths from an arbitrary starting point to an arbitrary end point. >

Evolutionary algorithm for path planning in mobile robot environment

Abstract: An evolutionary algorithm is discussed for the path planning problem in mobile robot environment, which may contain a number of unknown obstacles. The evolutionary algorithm searches for paths in the entire, continuous free space. It unifies off-line and on-line planning processes and provides high safety measures without requiring complete information about the obstacles sensed. >

Multistrategy adaptive path planning

Abstract: In 1990, we started the Router project, a multistrategy-strategy adaptive navigation path planner. It assumes that a mission planner has generated a specific mission plan and identified specific path planning tasks. Given a specific path planning task, it uses a combination of model based and case based methods to solve it. New versions of the Router system view strategic metacontrol as a kind of design task that takes as input a specification of a problem solving task and gives as output the specification of a virtual architecture for addressing it. One version of the system operates in simulated navigation worlds and provides a simple natural language interface. Another version is embodied in Stimpy, an autonomous mobile robot. Stimpy addresses issues in spatial navigation beyond path planning, such as plan execution and monitoring. Our goal is to describe our general framework of multistrategy adaptive path planning, and the specific design of the Router system. To focus this discussion, we report on a series of experiments with Router in simulated navigation worlds. >

Internal correction of dead-reckoning errors with the smart encoder trailer

Abstract: This paper presents an innovative method for accurate mobile robot dead-reckoning, called internal position error correction (IPEC). In previous work, the IPEC method was successfully implemented on a specially designed mobile robot with two differential drive axles, called the multi-degree-of-freedom (MDOF) mobile robot. Experimental results with the MDOF robot showed consistently one to two orders of magnitude better dead-reckoning accuracy than systems based on conventional dead-reckoning. Yet, the IPEC system requires neither external references (such as navigation beacons, artificial landmarks, known floorplans, or satellite signals), nor inertial navigation aids (such as accelerometers or gyros). This paper focuses on our current efforts to implement the IPEC method on a device that can be added to any existing mobile robot. This device, called the "Smart Encoder Trailer" (SET), is a small, single-axle trailer with an incremental encoder on each of its two wheels. Although the SET is not functional yet, simulation results combined with experimental results from the (similarly configured) MDOF vehicle strongly suggest the feasibility of the SET implementation. >

Robot navigation by conditional sequencing

Abstract: We investigate the application of conditional sequencing to robot navigation. Initial experimental results indicate that very robust navigation can be achieved by layering a conditional sequencer on top of a set of simple sensorimotor behaviors. The approach is uniquely flexible, permitting very complex tasks to be programmed reliably in very short periods of time. The technique was used in the recent American Association of Artificial Intelligence mobile robot contest. All of the contest-specific code was written in three days by a single programmer. The robot turned in the best overall performance of any entry. In addition, we present the results of over ninety formal experimental runs performed under a variety of circumstances. >

Autonomous sonar navigation in indoor, unknown and unstructured environments

Abstract: A mobile robot operating autonomously in unknown, unstructured environments has to be able to map its environment while at the same time determining its own position accurately within this environment. This paper presents an approach where the bootstrapping problem of concurrent localisation and map building is solved by estimating the respective errors introduced by each of the processes and correcting them accordingly. The success of this approach also hinges on the ability to determine which measurement originates from which feature. A heuristic multiple hypothesis data association framework is developed to deal with this problem. The problems encountered with the implementation of the algorithms on the mobile robot ROAMER are discussed. Real experiments in typical office environments have shown that the robot is able to navigate autonomously in such indoor environments. >

Quantitative evaluation of the exploration strategies of a mobile robot

Abstract: This article describes an experimental investigation into the map-building and exploration capabilities of a mobile robot. Two types of map are used: a set of line and point features, and a grid-ba...

Positioning by tree detection sensor and dead reckoning for outdoor navigation of a mobile robot

Abstract: We propose a positioning method for outdoor navigation of a mobile robot, by fusing dead reckoning and the tree detection sensor which consists of sonar and vision. A street lined with trees is assumed to be the mobile robot's outdoor work space. In this environment, trees are good landmarks for robot's position estimation. This paper describes a method for robot position estimation by fusion of dead reckoning and tree detection sensor based on maximum likelihood estimation at first. Then, the method for the detection of tree using the sensor system with sonar and vision mounted in one body is described. At last, the experimental results of self-guidance with the experimental autonomous mobile robot "YAMABICO" is presented. The result shows the effectiveness of the our method for outdoor navigation of the mobile robot. >

Why is it so difficult for a robot to pass through a doorway using ultrasonic sensors

Abstract: Complex tasks are usually described as high-level goals, leaving out the details on how to achieve them. However, to control a robot, details must be provided. Having the robot move itself to and through an unknown, and possibly narrow, doorway is an example of such a task. The authors illustrate the difficulty of such a task using actual data from a real robot. The authors show how the transformation from high-level goals to primitive commands can be performed at execution time and they propose an architecture based on reconfigurable objects that contain domain knowledge and knowledge about the sensors and actuators available. The authors then show how their approach is used in solving the illustrated task. >

Autonomous navigation in outdoor environment: adaptive approach and experiment

Abstract: This paper presents the approach, algorithms and processes we developed to perform cross-country autonomous navigation. After a presentation of the teleprogramming context, we introduce an adaptive navigation approach, well suited for the characteristics of complex natural environments. The main perception, motion planning and decisional processes required by the robot during navigation are briefly presented. An on board control architecture that manages all these processes is then described, and first results of an experiment currently developed at LAAS are discussed. >

Behavior of a mobile robot navigated by an "iterated forecast and planning" scheme in the presence of multiple moving obstacles

Abstract: This paper investigates behavior of a single mobile robot which is navigated by an "iterated forecast and planning" scheme in an environment where multiple obstacles are moving around. This navigation scheme, which was previously proposed by the authors, searches a feasible path for a robot in (x,y,t) space by a heuristic method. The movement of each obstacle is then forecasted under the assumption that it moves with a piecewise constant velocity. The planning algorithm is iterated frequently to accommodate the actual changes in the obstacles' velocity. This paper examines various kinds of the behavior obtained by different experimental conditions in the computer simulations. >