Showing papers on "Mobile robot published in 1999"

Monte Carlo localization for mobile robots

Abstract: To navigate reliably in indoor environments, a mobile robot must know where it is. Thus, reliable position estimation is a key problem in mobile robotics. We believe that probabilistic approaches are among the most promising candidates to providing a comprehensive and real-time solution to the robot localization problem. However, current methods still face considerable hurdles. In particular the problems encountered are closely related to the type of representation used to represent probability densities over the robot's state space. Earlier work on Bayesian filtering with particle-based density representations opened up a new approach for mobile robot localization based on these principles. We introduce the Monte Carlo localization method, where we represent the probability density involved by maintaining a set of samples that are randomly drawn from it. By using a sampling-based representation we obtain a localization method that can represent arbitrary distributions. We show experimentally that the resulting method is able to efficiently localize a mobile robot without knowledge of its starting location. It is faster, more accurate and less memory-intensive than earlier grid-based methods,.

Monte Carlo localization: efficient position estimation for mobile robots

Abstract: This paper presents a new algorithm for mobile robot localization, called Monte Carlo Localization (MCL). MCL is a version of Markov localization, a family of probabilistic approaches that have recently been applied with great practical success. However, previous approaches were either computationally cumbersome (such as grid-based approaches that represent the state space by high-resolution 3D grids), or had to resort to extremely coarse-grained resolutions. Our approach is computationally efficient while retaining the ability to represent (almost) arbitrary distributions. MCL applies sampling-based methods for approximating probability distributions, in a way that places computation "where needed." The number of samples is adapted on-line, thereby invoking large sample sets only when necessary. Empirical results illustrate that MCL yields improved accuracy while requiring an order of magnitude less computation when compared to previous approaches. It is also much easier to implement.

Markov localization for mobile robots in dynamic environments

Abstract: Localization, that is the estimation of a robot's location from sensor data, is a fundamental problem in mobile robotics. This papers presents a version of Markov localization which provides accurate position estimates and which is tailored towards dynamic environments. The key idea of Markov localization is to maintain a probability density over the space of all locations of a robot in its environment. Our approach represents this space metrically, using a fine-grained grid to approximate densities. It is able to globally localize the robot from scratch and to recover from localization failures. It is robust to approximate models of the environment (such as occupancy grid maps) and noisy sensors (such as ultrasound sensors). Our approach also includes a filtering technique which allows a mobile robot to reliably estimate its position even in densely populated environments in which crowds of people block the robot's sensors for extended periods of time. The method described here has been implemented and tested in several real-world applications of mobile robots, including the deployments of two mobile robots as interactive museum tour-guides.

MINERVA: a second-generation museum tour-guide robot

Abstract: This paper describes an interactive tour-guide robot, which was successfully exhibited in a Smithsonian museum. During its two weeks of operation, the robot interacted with thousands of people, traversing more than 44 km at speeds of up to 163 cm/sec. Our approach specifically addresses issues such as safe navigation in unmodified and dynamic environments, and short-term human-robot interaction. It uses learning pervasively at all levels of the software architecture.

Sliding mode control for trajectory tracking of nonholonomic wheeled mobile robots

Abstract: Nonholonomic mobile robots have constraints imposed on the motion that are not integrable, i.e., the constraints cannot be written as time derivatives of some function of the generalized coordinates. The position control of nonholonomic mobile robots has been an important class of control problems. In this paper, we propose a robust tracking control of nonholonomic wheeled mobile robots using sliding mode. The posture of a mobile robot is represented by polar coordinates and the dynamic equation of the robot is feedback-linearized by the computed-torque method. A novel sliding mode control law is proposed for asymptotically stabilizing the mobile robot to a desired trajectory. It is shown that the proposed scheme is robust to bounded external disturbances. Experimental results demonstrate the effectiveness of accurate tracking capability and the robust performance of the proposed scheme.

Continuum robots - a state of the art

Abstract: Like the human limbs which inspired them most robots are discrete mechanisms with rigid links connected by single degree of freedom joints. In contrast, 'continuum' and 'serpentine' robot mechanisms move by bending through a series of continuous arcs producing motion which resembles that of biological tentacles or snakes. This paper provides a single reference to the expanding technology of continuum robot mechanisms. It defines the fundamental difference between discrete, serpentine and continuum robot devices, presents the 'state of the art' of continuum robots, outlines their areas of application, and introduces some control issues. Finally, some conclusions regarding the continued development of these devices are made.

Distributed memoryless point convergence algorithm for mobile robots with limited visibility

Abstract: We present a distributed algorithm for converging autonomous mobile robots with limited visibility toward a single point. Each robot is an omnidirectional mobile processor that repeatedly: 1) observes the relative positions of those robots that are visible; 2) computes its new position based on the observation using the given algorithm; 3) moves to that position. The robots' visibility is limited so that two robots can see each other if and only if they are within distance V of each other and there are no other robots between them. Our algorithm is memoryless in the sense that the next position of a robot is determined entirely from the positions of the robots that it can see at that moment. The correctness of the algorithm is proved formally under an abstract model of the robot system in which: 1) each robot is represented by a point that does not obstruct the view of other robots; 2) the robots' motion is instantaneous; 3) there are no sensor and control error; 4) the issue of collision is ignored. The results of computer simulation under a more realistic model give convincing indication that the algorithm, if implemented on physical robots, will be robust against sensor and control error.

High-speed navigation using the global dynamic window approach

Abstract: Many applications in mobile robotics require the safe execution of a collision-free motion to a goal position. Planning approaches are well suited for achieving a goal position in known static environments, while real-time obstacle avoidance methods allow reactive motion behavior in dynamic and unknown environments. This paper proposes the global dynamic window approach as a generalization of the dynamic window approach. It combines methods from motion planning and real-time obstacle avoidance to result in a framework that allows robust execution of high-velocity, goal-directed reactive motion for a mobile robot in unknown and dynamic environments. The global dynamic window approach is applicable to nonholonomic and holonomic mobile robots.

Distributed Anonymous Mobile Robots

Abstract: Consider a system of multiple mobile robots in which each robot, at infinitely many unpredictable time instants, observes the positions of all the robots and moves to a new position determined by t...

The NavChair Assistive Wheelchair Navigation System

Abstract: The NavChair Assistive Wheelchair Navigation System is being developed to reduce the cognitive and physical requirements of operating a power wheelchair for people with wide ranging impairments that limit their access to powered mobility. The NavChair is based on a commercial wheelchair system with the addition of a DOS-based computer system, ultrasonic sensors, and an interface module interposed between the joystick and power module of the wheelchair. The obstacle avoidance routines used by the NavChair in conjunction with the ultrasonic sensors are modifications of methods originally used in mobile robotics research. The NavChair currently employs three operating modes: general obstacle avoidance, door passage, and automatic wall following. Results from performance testing of these three operating modes demonstrate their functionality. In additional to advancing the technology of smart wheelchairs, the NavChair has application to the development and testing of "shared control" systems where a human and machine share control of a system and the machine can automatically adapt to human behaviors.

Development of a bipedal humanoid robot-control method of whole body cooperative dynamic biped walking

Abstract: The authors have focused on the bipedal humanoid robot expected to play an active role in human living space, through studies on an anthropomorphic biped walking robot. As the first stage of developing a bipedal humanoid robot, the authors developed the human-size 35 active DOF bipedal humanoid robot "WABIAN" and the human-size 41 active DOF bipedal humanoid robot "WABIAN-R". The authors also proposed a basic control method of whole body cooperative dynamic biped walking that uses trunk or trunk-waist cooperative motion to compensate for three-axis (pitch, roll and yaw-axis) moment generated not only by the motion of the lower-limbs planned arbitrarily but by the time trajectory of the hands planned arbitrarily. Using these systems and the control method, normal biped walking (forward and backward), dynamic dance, waving arms and hip, dynamic carrying of a load using its arms, and trunk-waist cooperative dynamic walking are achieved.

The SPmap: a probabilistic framework for simultaneous localization and map building

Abstract: This article describes a rigorous and complete framework for the simultaneous localization and map building problem for mobile robots: the symmetries and perturbation map (SPmap), which is based on a general probabilistic representation of uncertain geometric information. We present a complete experiment with a LabMate/sup TM/ mobile robot navigating in a human-made indoor environment and equipped with a rotating 2D laser rangefinder. Experiments validate the appropriateness of our approach and provide a real measurement of the precision of the algorithms.

M+: a scheme for multi-robot cooperation through negotiated task allocation and achievement

Abstract: We present and discuss a distributed scheme for multi-robot cooperation. It integrates mission planning and task refinement as well as cooperative mechanisms adapted from the contract net protocol framework. We discuss its role and how it can be integrated as a component of a complete robot control system. We also discuss how it handles distributed task allocation and achievement as well as cooperative reaction to contingencies. Finally, we illustrate its use through a simulated system, which allows a number of robots to perform load transfer tasks in a route network environment.

Development and experimental validation of an adaptive extended Kalman filter for the localization of mobile robots

Abstract: A basic requirement for an autonomous mobile robot is its capability to elaborate the sensor measures to localize itself with respect to a coordinate system. To this purpose, the data provided by odometric and sonar sensors are here fused together by means of an extended Kalman filter. The performance of the filter is improved by an online adjustment of the input and measurement noise covariances obtained by a suitably defined estimation algorithm.

Active global localisation for a mobile robot using multiple hypothesis tracking

Abstract: In this paper we present a probabilistic approach for mobile robot localization using an incomplete topological world model. The method, which we have termed multi-hypothesis localization (MHL), us ...

Using the CONDENSATION algorithm for robust, vision-based mobile robot localization

Abstract: To navigate reliably in indoor environments, a mobile robot must know where it is. This includes both the ability of globally localizing the robot from scratch, as well as tracking the robot's position once its location is known. Vision has long been advertised as providing a solution to these problems, but we still lack efficient solutions in unmodified environments. Many existing approaches require modification of the environment to function properly, and those that work within unmodified environments seldomly address the problem of global localization. In this paper we present a novel, vision-based localization method based on the CONDENSATION algorithm, a Bayesian filtering method that uses a sampling-based density representation. We show how the CONDENSATION algorithm can be rued in a novel way to track the position of the camera platform rather than tracking an object in the scene. In addition, it can also be used to globally localize the camera platform, given a visual map of the environment. Based on these two observations, we present a vision-based robot localization method that provides a solution to a difficult and open problem in the mobile robotics community. As evidence for the viability of our approach, we show both global localization and tracking results in the context of a state of the art robotics application.

A Cooperative Hunting Behavior by Mobile-Robot Troops

Abstract: This paper presents a novel feedback-control law for coordinating the motion of multiple holonomic mobile robots to capture/enclose a target by making troop formations. This motion coordination is a cooperative behavior for security against invaders in surveillance areas. Each robot in this control law has its own coordinate system and it senses a target/invader, other robots and obstacles, to achieve this cooperative behavior without making any collision. Although there is no centralized controller and each robot has local feedback that is relative-position feedback, all the robots are asymptotically stabilized, and they make formations enclosing a target. Each robot especially has a vector referred to as a “formation vector,” and the formations are controllable by the vectors. As for determining the formation vectors, we use a reactive-control framework in which robots have some reactions heuristically designed according to this cooperative behavior. Therefore, this robotic system is a hybrid system tha...

Trajectory tracking control of a four-wheel differentially driven mobile robot

Abstract: We consider the trajectory tracking control problem for a 4-wheel differentially driven mobile robot moving on an outdoor terrain. A dynamic model is presented accounting for the effects of wheel skidding. A model-based nonlinear controller is designed, following the dynamic feedback linearization paradigm. An operational nonholonomic constraint is added at this stage, so as to obtain a predictable behavior for the instantaneous center of rotation thus preventing excessive skidding. The controller is then robustified, using conventional linear techniques, against uncertainty in the soil parameters at the ground-wheel contact. Simulation results show the good performance in tracking spline-type trajectories on a virtual terrain with varying characteristics.

Coastal navigation-mobile robot navigation with uncertainty in dynamic environments

Abstract: Ships often use the coasts of continents for navigation in the absence of better tools such as GPS, since being close to land allows sailors to determine with high accuracy where they are. Similarly for mobile robots, in many environments global and accurate localization is not always feasible. Environments can lack features, and dynamic obstacles such as people can confuse and block sensors. We demonstrate a technique for generating trajectories that take into account both the information content of the environment, and the density of the people in the environment. These trajectories reduce the average positional certainty as the robot moves, reducing the likelihood the robot will become lost at any point. Our method was successfully implemented and used by the mobile robot Minerva, a museum tourguide robot, for a 2 week period in the Smithsonian National Museum of American History.

H4: a new family of 4-DOF parallel robots

Abstract: This paper presents a new family of fully-parallel robots providing 3 translations and 1 rotation about a given axis. Such machines are aimed to use in robotics or machining. The ability of the proposed structure to provide the needed DOF is first proved. Position and velocity relationships are given. Finally, constructive designs are presented that show the effectiveness of the solution with either linear or rotational actuators; symmetrical and asymmetrical designs show that the H4 principle can be the base of a complete family of machines.

Micro inspection robot for 1-in pipes

Abstract: A micro inspection robot for 1-in pipes has been developed. The robot is 23 mm in diameter and 110 mm in length and is equipped with a high-quality micro charge-coupled device (CCD) camera and a dual hand for manipulating small objects in pipes. It can travel through both vertical pipes and curved sections, making possible inspections that would be difficult with conventional endoscopes. Its rate of travel is 6 mm/s and it has a load-pulling power of 1 N. To realize this microrobot, the authors have specially designed and developed several micro devices and micromechanisms: a novel micromechanism called a planetary wheel mechanism for robot drive; a micro electromagnetic motor with a micro planetary reduction gear to drive the planetary wheel mechanism; a micro pneumatic rubber actuator that acts as a hand; a micro CCD camera with high resolution; and a pneumatic wobble motor for rotating the camera and hands. In the paper, the design and performance of these micro devices are reported, the performance of the robot as a whole is described, and an application example is given.

Mobile robot and method for controlling a mobile robot

Abstract: A mobile robot includes an autonomous displacement device, a microphone, a loudspeaker, a mobile telephone module, and a voice analysis module able to interpret voice commands through the mobile telephone module to control the displacements of the mobile robot. The microphone is connected to the voice analysis module and thus also enables a human operator within earshot of the mobile robot to control the displacements of the mobile robot through voice commands.

On the Structure and Solution of the Simultaneous Localisation and Map Building Problem

Abstract: Paul Michael Newman Doctor of Philosophy The University of Sydney March 1999 On the Structure and Solution of the Simultaneous Localisation and Map Building Problem This thesis is concerned with the simultaneous localisation and map building (SLAM) problem. The SLAM problem asks if it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and then to incrementally build a map of this environment while simultaneously using this map to compute absolute vehicle location. The map and robot location estimates obtained from a successful SLAM system provide essential information upon which high level tasks such as path planning are predicated. A practicable solution to the SLAM problem is of inestimable value in the quest to create a truly autonomous mobile robot. The thesis has three principal theoretical contributions. The first is the elucidation of the structure of the SLAM problem. This is achieved by the analysis of a conventional and well known SLAM algorithm using global coordinates called, in this thesis, the Absolute Map Filter or AMF. Using this algorithm, three convergence theorems central to the SLAM problem are proved for the first time. They prove that the uncertainty in the estimated map decreases monotonically and achieves a defined lower bound. Futhermore, in the limit as the number of landmark observations increases, the relationship between landmarks becomes perfectly known. These proofs constitute the second theoretical contribution of the thesis. The third principal theoretical contribution of this thesis is the development of a novel SLAM solution capable of solving the SLAM problem in real time. This algorithm is called the Geometric Projection Filter or GPF. Rather than estimate the location of landmarks in global coordinates it estimates the relationships between individual landmarks. The convergence properties of this algorithm are derived and compared with those of the conventional AMF algorithm. An implementation of the GPF and the AMF is provided on a custom built subsea vehicle. The performance of the two filters are compared and shown to have the properties predicted by the preceding theoretical analysis. This implementation constitutes the fourth principal contribution of the thesis. It shows that the GPF can be used as the basis of a substantive real time deployment of a mobile robot in an initially unknown environment.

Using autonomous robotics to teach science and engineering

Abstract: f you walked into our Autonomous Robotics class at Case Western Reserve University on a typical day, you might be surprised to find 30 college students from a variety of engineering and science disciplines sitting on the floor surrounded by LEGO blocks. Appearances can be deceiving; this course tackles serious issues in engineering and science education. In this course, students design, build, program and test their own autonomous robots that participate in a public competition. This course uses robotics to foster a hands-on, interdisciplinary, teamwork-oriented approach to the synthesis and analysis of integrated real-world systems, as well as teaching new approaches to robot control. Created in 1995, our Autonomous Robotics course grew out of ongoing research on biologically inspired robotics at CWRU [3]. The design of this course draws heavily on technology developed at MIT, first for K–12 education [11] and later for an undergraduate course similar to ours that has been offered since 1990 [8]. Related courses have been developed at the University of Edinburgh [7] and elsewhere. Two features of our course distinguish it from these other courses. First, our final competition is considerably more technically demanding. Second, we address a much broader set of educational goals. Our course attracts students from computer engineering and science, biology, electrical engineering, neuroscience, systems engineering, biomedical engineering, and physics. In this article, we describe the educational goals of the course, its overall design, the final competition, and student assessment.

A high stability, smooth walking pattern for a biped robot

Abstract: Biped robots have better mobility than conventional wheeled robots, but they tip over easily. In order to walk stably in various environments such as rough terrain, up and down slopes, or regions containing obstacles, it is desirable to adapt to such ground conditions with a suitable foot motion, and maintain the stability of the robot by a smooth hip motion. We propose a method to plan a walking pattern consisting of a foot trajectory and a hip trajectory. First, we formulate the constraints of a foot trajectory, and generate the foot trajectory by 3rd order spline interpolation. By setting the values of constraint parameters, it is easy to produce different types of foot motion. Then, we formulate a hip trajectory using a 3rd order periodic spline function, and derive the hip trajectory with high stability. Finally, the effectiveness of the proposed method is illustrated by simulation examples.

Robust localization using relative and absolute position estimates

Abstract: A low cost strategy based on well calibrated odometry is presented for localizing mobile robots The paper describes a two-step process for correction of 'systematic errors' in encoder measurements followed by fusion of the calibrated odometry with a gyroscope and GPS resulting in a robust localization scheme A Kalman filter operating on data from the sensors is used for estimating position and orientation of the robot Experimental results are presented that show an improvement of at least one order of magnitude in accuracy compared to the un-calibrated, un-filtered case Our method is systematic, simple and yields very good results We show that this strategy proves useful when the robot is using GPS to localize itself as well as when GPS becomes unavailable for some time As a result robot can move in and out of enclosed spaces, such as buildings, while keeping track of its position on the fly

Circumventing dynamic modeling: evaluation of the error-state Kalman filter applied to mobile robot localization

Abstract: The mobile robot localization problem is treated as a two-stage iterative estimation process. The attitude is estimated first and is then available for position estimation. The indirect (error state) form of the Kalman filter is developed for attitude estimation when applying gyro modeling. The main benefit of this choice is that combined dynamic modeling of the mobile robot and its interaction with the environment is avoided. The filter optimally combines the attitude rate information from the gyro and the absolute orientation measurements. The proposed implementation is independent of the structure of the vehicle or the morphology of the ground. The method can easily be transferred to another mobile platform provided it carries an equivalent set of sensors. The 2D case is studied in detail first. Results of extending the approach to the 3D case are presented. In both cases the results demonstrate the efficacy of the proposed method.

Exponential Stabilization of a Wheeled Mobile Robot Via Discontinuous Control

Abstract: In the present work the problem of exponential stabilization of the kinematic and dynamic model of a simple wheeled mobile robot is addressed and solved using a discontinuous, bounded, time invariant, state feedback control law. The properties of the closed-loop system are studied in detail and its performance in presence of model errors and noisy measurements are evaluated and discussed.

An intelligent robotic system based on a fuzzy approach

Abstract: This paper deals with a fuzzy-based intelligent robotic system that requires various capabilities normally associated with intelligence. It acquires skills and knowledge through interaction with a dynamic environment. Subsumption architectures, behavior-based artificial intelligence, and behavioral engineering for robotic systems have been discussed as new technologies for intelligent robotic systems. This paper proposes a robotic system with "structured intelligence". We focus on a mobile robotic system with a fuzzy controller and propose a sensory network that allows the robot to perceive its environment. An evolutionary approach improves the robot's performance. Furthermore, we discuss the effectiveness of the proposed method through computer simulations of collision avoidance and path-planning problems.