Showing papers on "Mobile robot published in 1988"

Sensor fusion in certainty grids for mobile robots

Abstract: A numeric representation of uncertain and incomplete sensor knowledge called certainty grids was used successfully in several recent mobile robot control programs developed at the Carnegie-Mellon University Mobile Robot Laboratory (MRL). Certainty grids have proven to be a powerful and efficient unifying solution for sensor fusion, motion planning, landmark identification, and many other central problems. MRL had good early success with ad hoc formulas for updating grid cells with new information. A new Bayesian statistical foundation for the operations promises further improvement. MRL proposes to build a software framework running on processors onboard the new Uranus mobile robot that will maintain a probabilistic, geometric map of the robot's surroundings as it moves. The certainty grid representation will allow this map to be incrementally updated in a uniform way based on information coming from various sources, including sonar, stereo vision, proximity, and contact sensors. The approach can correctly model the fuzziness of each reading and, at the same time, combine multiple measurements to produce sharper map features; it can also deal correctly with uncertainties in the robot's motion. The map will be used by planning programs to choose clear paths, identify locations (by correlating maps), identify well-known and insufficiently sensed terrain, and perhaps identify objects by shape. The certainty grid representation can be extended in the time dimension and used to detect and track moving objects. Even the simplest versions of the idea allow us to fairly straightforwardly program the robot for tasks that have hitherto been out of reach. MRL looks forward to a program that can explore a region and return to its starting place, using map "snapshots" from its outbound journey to find its way back, even in the presence of disturbances of its motion and occasional changes in the terrain.

Vision and navigation for the Carnegie-Mellon Navlab

Abstract: A distributed architecture articulated around the CODGER (communication database with geometric reasoning) knowledge database is described for a mobile robot system that includes both perception and navigation tools. Results are described for vision and navigation tests using a mobile testbed that integrates perception and navigation capabilities that are based on two types of vision algorithms: color vision for road following, and 3-D vision for obstacle detection and avoidance. The perception modules are integrated into a system that allows the vehicle to drive continuously in an actual outdoor environment. The resulting system is able to navigate continuously on roads while avoiding obstacles. >

Obstacle avoidance with ultrasonic sensors

Abstract: A mobile robot system, capable of performing various tasks for the physically disabled, has been developed. To avoid collision with unexpected obstacles, the mobile robot uses ultrasonic range finders for detection and mapping. The obstacle avoidance strategy used for this robot is described. Since this strategy depends heavily on the performance of the ultrasonic range finders, these sensors and the effect of their limitations on the obstacle avoidance algorithm are discussed in detail. >

Dynamically reconfigurable robotic system

Abstract: The concept of the DRRS (dynamically reconfigurable robotic system) based on a cell structure is proposed for the next generation of robotic systems. The system can reorganize its configuration and its software to a given task, so that its level of flexibility and adaptability is much higher than that of the conventional robots. It consists of a lot of intelligent cells that have a fundamental mechanical function. Each cell can detach itself and recombine autonomously, depending on a task, e.g. To provide manipulators or mobile robots. The system can also be self-repairing and fault-tolerant. A decision method for cell-structured-manipulator configurations is proposed. >

Building, registrating, and fusing noisy visual maps

Abstract: This paper deals with the problem of building three-dimen sional descriptions (we call them visual maps) of the environ ment of a mobile robot using passive vision. These maps are local (i.e., attached to specific frames of reference). Since noise is present, they incorporate information about the ge ometry of the environment and about the uncertainty of the parameters defining the geometry. This geometric uncertainty is directly related to its source (i.e., sensor uncertainty). We show how visual maps corresponding to different positions of the robot can be registered to compute a better estimate of its displacement between the various viewpoint positions, as suming an otherwise static environment. We use these esti mates to fuse the different visual maps and reduce locally the uncertainty of the geometric primitives which have found correspondents in other maps. We propose to perform these three tasks (building, registrating, and fusing visual maps) within the general framework of extended Kalman filter...

Combining sonar and infrared sensors for mobile robot navigation

Abstract: Multiple sensors can be used on a mobile robot so that it can perceive its environment with better accuracy than if either sensor were used alone. Sonar and infrared sensors are used here in a comp...

Maintaining representations of the environment of a mobile robot

Abstract: A description is given of current ideas related to the problem of building and updating three-dimensional representations of the environment of a mobile robot that uses passive vision as its main sensory modality. The authors attempt to represent both geometry and uncertainty. The authors motivate their approach by defining the problems they are trying to solve and then give some simple didactic examples. They then present a tool they think is extremely well adapted to solving most of these problems: the extended Kalman filter (EKF). The authors discuss the notions of minimal geometric representations for three-dimensional lines, planes, and rigid motions. They show how the EKF and the representations can be combined to provide solutions for some of the problems. A number of experimental results on real data are given. >

Modal Control Of An Attentive Vision System

Abstract: Cambridge, MA A vision system for use in a mobile robot system, or in n fixed multi-tasking industrial robot requires attentive control. Attentive control refers to the process by which the direction of gaze of the visual sensors are determined, nlong with the determination of what processing is required to be applied to the sensed images based on the goals of the robot and the tasks it is performing. This paper describes the implementation of a. mnt,ion control system which allows the attentive control of a binocular vision system. Attentive inputs to the system specify the type of visual feedback that the oculo-motor control system will use. The MDL language developed by Brockett [7] i8 used to communicate between the attentive planner and the motion controller.

Location estimation and uncertainty analysis for mobile robots

Abstract: A motion controller for the autonomous mobile vehicle commands the robot's drive mechanism to keep the robot near its desired path at all times. In order for the controller to behave properly, the controller must know the robot's position at any given time. The controller uses the information provided by the optical encoders attached to the wheels to determine vehicle position. The author analyzes the effect of measurement errors, wheel slippage, and noise on the accuracy of the estimated vehicle position obtained in this manner. Specifically the location estimator and its uncertainty covariance matrix are derived. >

A Robot Ping-Pong Player: Experiments in Real-Time Intelligent Control

Abstract: This tour de force in experimental robotics paves the way toward understanding dynamic environments in vision and robotics. It describes the first robot able to play, and even beat, human ping-pong players.Constructing a machine to play ping-pong was proposed years ago as a particularly difficult problem requiring fast, accurate sensing and actuation, and the intelligence to play the game. The research reported here began as a series of experiments in building a true real-time vision system. The ping-pong machine incorporates sensor and processing techniques as well as the techniques needed to intelligently plan the robot's response in the fraction of a second available. it thrives on a constant stream of new data. Subjectively evaluating and improving its motion plan as the data arrives, it presages future robot systems with many joints and sensors that must do the same, no matter what the task.Contents: Introduction. Robot Ping-Pong. System Design. Real-Time Vision System Robot Controller. Expert Controller Preliminaries. Expert Controller. Robot Ping-Pong Application. Conclusion.Russell L. Andersson is Member of Technical Staff, Robotics Systems Research Department, AT&T Bell Laboratories. "A Robot Ping-Pong Player" is included in the Artificial Intelligence Series, edited by Patrick Winston and Michael Brady.

A robust, qualitative method for robot spatial learning

Abstract: We present a qualitative method for a mobile robot to explore an unknown environment and learn a map, which can be robust in the face of various possible errors in the real world. Procedural knowledge for the movement, topological model for the structure of the environment, and metrical information for geometrical accuracy are separately represented in our method, whereas traditional methods describe the environment mainly by metrical information. The topological model consists of distinctive places and local travel edges linking nearby distinctive places. A distinctive place is defined as the local maximum of some measure of distinctiveness appropriate to its immediate neighborhood, and is found by a hill-climbing search. Local travel edges are defined in terms of local control strategies required for travel. How to find distinctive places and follow edges is the procedural knowledge which the robot learns dynamically during exploration stage and guides the robot in the navigation stage. An accurate topological model is created by linking places and edges, and allows metrical information to be accumulated with reduced vulnerability to metrical errors. We describe a working simulation in which a robot, NX, with range sensors explores a variety of 2-D environments and we give its successful results under varying levels of random sensor error.

Some location problems for robot navigation using a single camera

Abstract: The paper considers two classes of point location problems found in visual navigation of a mobile robot. The problems we consider are finding the location of a robot using a map of the room where the robot moves and an image taken by a camera carried by the robot. In the first class of problems, vertical edges in the image are given, and a possible location for the robot is investigated by establishing a correspondence between the edges in the images and vertical poles given in the map. In the second class of problems, the possible region for the robot is investigated under the assumption that vertical edges are distinguishable from each other, but only the order in which the edges are found when the image is swept from left to right is given. These problems and their variations are considered from a computational geometry point of view, and efficient algorithms for solving them are given.

Landmark recognition for autonomous mobile robots

Abstract: A novel approach for landmark recognition based on the perception, reasoning, action, and expectation (PREACTE) paradigm is presented for the navigation of autonomous mobile robots. PREACTE uses expectations to predict the appearance and disappearance of objects, thereby reducing computational complexity and locational uncertainty. It uses an innovative concept called dynamic model matching (DMM), which is based on the automatic generation of landmark description at different ranges and aspect angles and uses explicit knowledge about maps and landmarks. Map information is used to generate an expected site model (ESM) for search delimitation, given the location and velocity of the mobile robot. The landmark recognition vision system generates 2-D and 3-D scene models from the observed scene. The ESM hypotheses are verified by matching them to the image model. Experimental results that verify the performance of the PREACTE and DMM algorithms for real imagery are also presented. >

Region filling operations with random obstacle avoidance for mobile robots

Abstract: The article presents a new topic in path planning for mobile robots, region filling. which involves a sweeping operation to fill a whole region with random obstacle avoidance. The approaches for global strip filling and local path searching driven by sensory data procedures are developed. A computer graphic simulation is used to verify the filling strategy available. The research was developed from the program for the design of a robot lawn mower. However, the solution appears generic. The significance is that a problem of wide application and generic solutions for general autonomous mobile robots have been developed.

Local path control for an autonomous vehicle

Abstract: A control system for an autonomous robot cart designed to operate in well-structured environments such as offices and factories is described. The onboard navigation system comprises a reference-state generator, an error-feedback controller, and cart-location sensing using odometry. There is a convenient separation between the path guidance and control logic. Under normal operating conditions, the controller ensures that the errors between the measured and reference states are small. These errors only exceed set limits if the cart is malfunctioning. Major hardware failures can be detected in this way and failsafe procedures invoked. Results on the control system performance derived from a computer simulation of the cart and its operating environment, and from an experimental cart, indicate that the system can provide reliable, accurate, and safe operation. >

Planning collision-free trajectories in time-varying environments: a two-level hierarchy

Abstract: Global geometric algorithms for trajectory planning are used in conjunction with a local avoidance strategy. Simulations have been developed for a mobile robot in the plane among stationary and moving obstacles. Essentially, the robot has a geometric planner that provides a coarse trajectory (the path and the velocity along it), which may be modified by a (low-level) local avoidance module if sensors detect obstacles in the vicinity of the robot. This hierarchy makes effective use of the complementarity between global trajectory planning and local obstacle avoidance. >

Pilot level of a hierarchical controller for an unmanned mobile robot

Abstract: The controller for an intelligent mobile autonomous system (IMAS), equipped with vision and low-level sensors to cope with unknown obstacles, is modeled as a hierarchy of decision-making for planning and control. One of the levels (pilot) deals with a distorted 'windshield' view of the world and provides the actuator controller with real-time decisions. This level of IMAS controller is treated as a linguistic controller with fuzzy variables that assume values from possible intervals. The decision-making process at this level of control are presented as a production system with a fuzzy database. The rules in the production system are derived from an analytical system model for minimum-time control. The choice of optimal motion execution commands is performed using fuzzy set operators. Also included is a temporal decision-making mechanism (reporter), which recognizes the persisting conflicts between successive levels of the hierarchy by observing the motion trajectory. >

Locomotion-command method for mobile robots

Abstract: A locomotion-command method for a mobile robot of the type having a master section and a locomotion module wherein a travelling route is specified by a command sent from the master section to the locomotion module and wherein travelling on a given direction line is set as a basic motion, and a travelling route can be arbitrarily set by sending a command which specifies changes in the position, direction and angle of the direction line, to thereby enable a robot to freely travel with simple commands and to realize effective control of the robot.

One dimensional image visual system for a moving vehicle

Abstract: A vision system for a mobile robot 10 comprises an optical sensor subsystem 20 which generates a substantially one dimensional image of an environment, a signal processing subsystem 24 for extracting and enhancing significant vertical visual features from the one dimensional image and a feature processing system 26 which analyses rapidly and in real time the extracted features for use by a control system 28 for navigation of the robot. The optical sensor may be a line scan camera having a plurality of outputs which relate to brightness values received from the environment. Triangulation, optical flow and optical flow with log transforms methods are disclosed for processing the one dimensional image data to yield azimuth and/or distance to an object within the environment. Also disclosed is a binocular vision system which generates two, one dimensional images and a method of processing same.

Traffic control of multiple robot vehicles

Abstract: The author addresses the control of traffic when there are large numbers of automatic guided vehicles (AGVs) in a factory. Several possible policies for managing AGVs to minimize the impact of traffic jams were analyzed. In a grid-iron network of roads, it is shown that traffic contention can have a large effect on the collective performance of AGVs. It is shown that a particular traffic policy permits the AGVs to be autonomous and independent while avoiding deadlocks. This policy is shown to be close to optimal, even for large numbers of vehicles. It is also shown under what conditions it is beneficial to modify the factory to have highways and superhighways. >

Analysis Of A Sequence Of Stereo Scenes Containing Multiple Moving Objects Using Rigidity Constraints

Abstract: Iri this paper, we describe a method for comput.ing the rriovc~rrient. of objects as well as that of a mobile robot from ii scqiicrice of stereo frames. Stereo frames are obtained at ~iifl’(~reiit, instants by a stereo rig, when the mobile robot rIilvigat(>s in an unknown environment possibly containing ~)iiit: rrioving rigid objects. An approach based on rigidity ( oiihlraiiit,s is presented for registering two stereo frames. Wcs dernoristrate how the uncertainty of measurements can IN^ integrated with the formalism of the rigidity constraints. A iiew technique is described to match very noisy segments. ‘1‘11~ iiifluence of egomotion on observed movement:; of ob,j(~ 1,s is discussed in detail. Egomotion is fir:jt determined itiid then eliminated before determination of the motion of o1)jt:cl.s. The proposed algorithm is completely automatic. I~:xperirnerital results are provided. Some remarks conclude ths paper.

Cleaning robot control

Abstract: A small and lightweight cleaning robot powered from the AC power supply is produced for testing purposes The robot provides a cable-length control function which prevents tangling of the cables during traveling, an ultrasonic sensor function which detects obstacles and dodges them, and a distance measuring function which makes it possible to run parallel to the wall In a simple room with few obstacles, the robot can travel even if it does not incorporate information but in areas with complicated placement of obstacles, it is necessary to teach the robot the obstacle positions and the room size in advance >

Using EEG alpha rhythm to control a mobile robot

Abstract: A report is presented of experiments in start/stop control of microrobot movement using EEG alpha waves. The robot is a trajectory-follower and uses an optical sensor. Experimental design allows the subject to start robot movement by closing his or her eyes and to stop the robot by opening them. EEG alpha wave recognition software controls the movement of the robot. >

Blanche: an autonomous robot vehicle for structured environments

Abstract: Blanche is an experimental vehicle designed to operate autonomously within a structured office or factory environment. Blanche has been designed with several goals in mind. First and foremost, Blanche is a testbed with which to experiment with such things as robot programming languages, sensor integration/data fusion techniques, i.e. the management of sparse, conflicting, and/or uncertain information, and with techniques for error detection and recovery. Second, Blanche is designed to be low-cost and its dependence on only two sensors, an optical rangefinder and odometry, reflects this. A description is given of the structure of the vehicle and its associated sensors. Experimental results characterizing the accuracy and repeatability of the cart and sensors are presented. A brief description of the obstacle-free trajectory generation and low-level control algorithms are also given. >

A paradigm for incorporating vision in the robot navigation function

Abstract: The authors present a paradigm for combining vision with motion planning. It turns out that extensive modifications of so-called tactile algorithms are needed to take full advantage of the additional sensing capabilities, while not sacrificing the algorithm convergence. Different design principles can be introduced that result in algorithm versions exhibiting different styles of behavior and producing different paths, without, in general, being superior to each other. >

Motion planning for a mobile robot with a kinematic constraint

Abstract: The motion planning problem is discussed for a mobile robot with a kinematic constraint, that is, the number of its degrees of freedom is less than the dimension of its configuration space. Addressing first the local problem of turning in a corridor, it is shown that sliding continuously on the outer wall in a turn constitutes a canonical contract trajectory, in the sense that if it is not safe, there cannot be another safe trajectory with no backing-up maneuver. For the case in which no smooth trajectory exists, some simple maneuvers are proposed. A heuristic path-planning algorithm based on a decomposition of free space into cones connected by turns is then presented. It is shown how this approach can be used within the more realistic framework of an actual mobile robot at work by implementing the results as a set of rules of behavior for the robot. >