Showing papers on "Robot published in 1996"

Probabilistic roadmaps for path planning in high-dimensional configuration spaces

Abstract: A new motion planning method for robots in static workspaces is presented. This method proceeds in two phases: a learning phase and a query phase. In the learning phase, a probabilistic roadmap is constructed and stored as a graph whose nodes correspond to collision-free configurations and whose edges correspond to feasible paths between these configurations. These paths are computed using a simple and fast local planner. In the query phase, any given start and goal configurations of the robot are connected to two nodes of the roadmap; the roadmap is then searched for a path joining these two nodes. The method is general and easy to implement. It can be applied to virtually any type of holonomic robot. It requires selecting certain parameters (e.g., the duration of the learning phase) whose values depend on the scene, that is the robot and its workspace. But these values turn out to be relatively easy to choose, Increased efficiency can also be achieved by tailoring some components of the method (e.g., the local planner) to the considered robots. In this paper the method is applied to planar articulated robots with many degrees of freedom. Experimental results show that path planning can be done in a fraction of a second on a contemporary workstation (/spl ap/150 MIPS), after learning for relatively short periods of time (a few dozen seconds).

Measurement and modeling of McKibben pneumatic artificial muscles

Abstract: This paper reports mechanical testing the modeling results for the McKibben artificial muscle pneumatic actuator. This device contains an expanding tube surrounded by braided cords. We report static and dynamic length-tension testing results and derive a linearized model of these properties for three different models. The results are briefly compared with human muscle properties to evaluate the suitability of McKibben actuators for human muscle emulation in biologically based robot arms.

Measurement and correction of systematic odometry errors in mobile robots

Abstract: Odometry is the most widely used method for determining the momentary position of a mobile robot. This paper introduces practical methods for measuring and reducing odometry errors that are caused by the two dominant error sources in differential-drive mobile robots: 1) uncertainty about the effective wheelbase; and 2) unequal wheel diameters. These errors stay almost constant over prolonged periods of time. Performing an occasional calibration as proposed here will increase the odometric accuracy of the robot and reduce operation cost because an accurate mobile robot requires fewer absolute positioning updates. Many manufacturers or end-users calibrate their robots, usually in a time-consuming and nonsystematic trial and error approach. By contrast, the method described in this paper is systematic, provides near-optimal results, and it can be performed easily and without complicated equipment. Experimental results are presented that show a consistent improvement of at least one order of magnitude in odometric accuracy (with respect to systematic errors) for a mobile robot calibrated with our method.

Relative end-effector control using Cartesian position based visual servoing

Abstract: This paper presents a complete design methodology for Cartesian position based visual servo control for robots with a single camera mounted at the end-effector. Position based visual servo control requires the explicit calculation of the relative position and orientation (POSE) of the workpiece object with respect to the camera. This is accomplished using image plane measurements of a number of known feature points on the object, and then applying an extended Kalman filter to obtain a recursive solution of the photogrammetric equations, and to properly combine redundant measurements. The control is then designed by specifying the desired trajectories with respect to the object and forming the control error in the end-effector frame. The implementation using a distributed computer architecture is described. An experimental system has been built and used to evaluate the performance of the POSE estimation and the position based visual servo control. Several results for relative trajectory control and target tracking are presented. Results of the experiments showing the effect of loss of some of the redundant features are also presented.

Analysis of probabilistic roadmaps for path planning

Abstract: Provides an analysis of a path planning method which uses probabilistic roadmaps. This method has proven very successful in practice, but the theoretical understanding of its performance is still limited. Assuming that a path /spl gamma/ exists between two configurations a and b of the robot, we study the dependence of the failure probability to connect a and b on (i) the length of /spl gamma/, (ii) the distance function of /spl gamma/ from the obstacles, and (iii) the number of nodes N of the probabilistic roadmap constructed. Importantly, our results do not depend strongly on local irregularities of the configuration space, as was the case with previous analysis. These results are illustrated with a simple but illuminating example. In this example, we provide estimates for N, the principal parameter of the method, in order to achieve failure probability within prescribed bounds. We also compare, through this example, the different approaches to the analysis of the planning method.

Estimating the absolute position of a mobile robot using position probability grids

Abstract: In order to re-use existing models of the environment mobile robots must be able to estimate their position and orientation in such models. Most of the existing methods for position estimation are based on special purpose sensors or aim at tracking the robot's position relative to the known starting point. This paper describes the position probability grid approach to estimating the robot's absolute position and orientation in a metric model of the environment. Our method is designed to work with standard sensors and is independent of any knowledge about the starting point. It is a Bayesian approach based on certainty grids. In each cell of such a grid we store the probability that this cell refers to the current position of the robot. These probabilities are obtained by integrating the likelihoods of sensor readings over time. Results described in this paper show that our technique is able to reliably estimate the position of a robot in complex environments. Our approach has proven to be robust with respect to inaccurate environmental models, noisy sensors, and ambiguous situations.

Evolution of homing navigation in a real mobile robot

Abstract: In this paper we describe the evolution of a discrete-time recurrent neural network to control a real mobile robot. In all our experiments the evolutionary procedure is carried out entirely on the physical robot without human intervention. We show that the autonomous development of a set of behaviors for locating a battery charger and periodically returning to it can be achieved by lifting constraints in the design of the robot/environment interactions that were employed in a preliminary experiment. The emergent homing behavior is based on the autonomous development of an internal neural topographic map (which is not pre-designed) that allows the robot to choose the appropriate trajectory as function of location and remaining energy.

Model-based learning for mobile robot navigation from the dynamical systems perspective

Abstract: This paper discusses how a behavior-based robot can construct a "symbolic process" that accounts for its deliberative thinking processes using models of the environment. The paper focuses on two essential problems; one is the symbol grounding problem and the other is how the internal symbolic processes can be situated with respect to the behavioral contexts. We investigate these problems by applying a dynamical system's approach to the robot navigation learning problem. Our formulation, based on a forward modeling scheme using recurrent neural learning, shows that the robot is capable of learning grammatical structure hidden in the geometry of the workspace from the local sensory inputs through its navigational experiences. Furthermore, the robot is capable of generating diverse action plans to reach an arbitrary goal using the acquired forward model which incorporates chaotic dynamics. The essential claim is that the internal symbolic process, being embedded in the attractor, is grounded since it is self-organized solely through interaction with the physical world. It is also shown that structural stability arises in the interaction between the neural dynamics and the environmental dynamics, which accounts for the situatedness of the internal symbolic process, The experimental results using a mobile robot, equipped with a local sensor consisting of a laser range finder, verify our claims.

Robust asymptotically stable visual servoing of planar robots

Abstract: In this paper we address the visual servoing of planar robot manipulators under fixed-camera configuration. The control goal is to place the robot end-effector over a desired static target by using a vision system equipped with a fixed camera to 'see' the robot end-effector and target. We analyze an image-based controller, whose implementation requires the robot Jacobian, the gravitational torque vector, and the camera orientation. Further, the robot manipulator is not treated as an ideal positioning device but modeled by the Lagrangian dynamics. We formally prove that the overall closed-loop system composed by the full nonlinear robot dynamics and the controller is Lyapunov stable. Also, we demonstrate that the controller is capable to yield an asymptotically stable system which is robust against radial lens distortions and uncertainty in the camera orientation. Simulations on a two degrees of freedom arm are presented to illustrate the controller performance.

The calibration index and taxonomy for robot kinematic calibration methods

Abstract: The major approaches toward kinematic calibration are unified by considering an end-point measurement system as forming a joint and closing the kinematic loop. A calibration index is in troduced, b...

Motion control of a spherical mobile robot

Abstract: The paper deals with dynamics and control of a special type of mobile robot designed to act as a small platform to carry sensing devices or actuators in an environment where stability of the platform is critical, like in surveying unstructured hostile industrial environment exploring other planets, or simply being a part of a human place, like office or home, which has not been designed for mobile machines. The spherical construction offers extraordinary motion properties in cases where turning over or falling down are risks for the robot to continue its motion. Also it has full capability to recover from collisions with obstacles or another robots traveling in the environment.

Virtual structures for high-precision cooperative mobile robotic control

Abstract: A key problem in cooperative robotics is the maintenance of a geometric configuration during movement. To address this problem, the concept of a virtual structure is introduced. Control methods are developed to force an ensemble of robots to behave as if they were particles embedded in a rigid structure. The method was tested both using simulation and experimentation with a set of three robots. Results are presented which demonstrate that this approach is capable of achieving high precision movement which is fault tolerant and exhibits graceful degradation of performance. In addition, this algorithm does not require leader selection as in other cooperative robotic strategies. Finally, the method is highly flexible in the kinds of geometric formations that can be maintained.

Visual Control of Robots: High-Performance Visual Servoing

Abstract: From the Publisher: This book is about the application of high-speed machine vision for close-loop position control, or visual servoing, of a robot manipulator. It provides a comprehensive coverage of all aspects of the visual servoing problem: robotics, vision, control, technology and implementation issues. While much of the discussion is quite general the experimental work described is based on the use of a high-speed binary vision system with a monocular "eye-in-hand" camera.

Distributed algorithms for formation of geometric patterns with many mobile robots

Abstract: We discuss a method for controlling a group of mobile robots in a distributed manner. The method is distributed in the sense that all robots, or most of the robots in some cases, plan their motion individually based upon the given goal of the group and the observed positions of other robots. We illustrate the method by showing how a large number of robots can form an approximation of a circle, a simple polygon, or a line segment in the plane. We also show how the robots can distribute themselves nearly uniformly within a circle or a convex polygon in the plane. Finally, we show how the robots can be divided into two or more groups. It turns out that in many cases most robots execute an identical, simple algorithm. The performance of the method is demonstrated by simulation. © 1996 John Wiley & Sons, Inc.

Purposive behavior acquisition for a real robot by vision-based reinforcement learning

Abstract: This paper presents a method of vision-based reinforcement learning by which a robot learns to shoot a ball into a goal. We discuss several issues in applying the reinforcement learning method to a real robot with vision sensor by which the robot can obtain information about the changes in an environment. First, we construct a state space in terms of size, position, and orientation of a ball and a goal in an image, and an action space is designed in terms of the action commands to be sent to the left and right motors of a mobile robot. This causes a “state-action deviation” problem in constructing the state and action spaces that reflect the outputs from physical sensors and actuators, respectively. To deal with this issue, an action set is constructed in a way that one action consists of a series of the same action primitive which is successively executed until the current state changes. Next, to speed up the learning time, a mechanism of Learning from Easy Missions (or LEM) is implemented. LEM reduces the learning time from exponential to almost linear order in the size of the state space. The results of computer simulations and real robot experiments are given.

Geometrical Methods in Robotics

Abstract: From the Publisher: This book provides an introduction to the geometrical concepts that are important to applications in robotics. The author shows how these concepts may be used to formulate and solve complex problems encountered in the design and construction of robots. The book begins by introducing a brief survey of algebraic and differential geometry and then the concept of the Lie group. Subsequent chapters develop the structure of Lie groups and how these relate to planar kinematics, line geometry, representation theory, and other topics. Having provided the conceptual framework, the author then demonstrates the power and elegance of these methods to robotics, notably to the statics and dynamics of robots, to the problems of gripping solid objects, to the numbers of postures of robots, and to screw systems. Graduate students in computer engineering and robotics will find this book an invaluable and modern introduction to this field. Researchers already working on problems in robotics will find the volume a useful reference source and a guide to more advanced topics.

Specification of force-controlled actions in the "task frame formalism"-a synthesis

Abstract: Autonomous robot tasks involving contacts with the environment must be performed under active force control if the geometric uncertainties in the task models are too large to cope with by means of passive compliance only. In practice, task specification of force-controlled actions is closely linked to the task frame formalism (TFF), also known as the compliance frame formalism. The TFF is a very intuitive and controller-independent approach to model a motion constraint, and to specify the desired forces and motions compatible with this constraint. However, it has never been defined clearly and unambiguously, and it cannot cope with all possible constrained motion tasks. This paper provides, for the first time, a formal definition of what makes up a TFF task specification. It gives also a synthesis of which tasks the TFF can cope with, and proposes a generic textual task specification formalism. Finally, it describes an example constrained motion task that the TFF cannot handle.

AMOS: comparison of scan matching approaches for self-localization in indoor environments

Abstract: This paper describes results from evaluating different self-localization approaches in indoor environments for mobile robots. The algorithms examined are based on 2D laser scans and an odometry position estimate and do not need any modifications in the environment. An important requirement for the self-localization is the ability to cope with office-like environments as well as with environments without orthogonal and rectilinear walls. Furthermore, the approaches have to be robust enough to cope with slight modifications in the daily environment and should be fast enough to be used online on board of the robot system. To fulfil these requirements we made some extensions to the existing approaches and combined them in a suitable manner. Real world experiments with our robot within the everyday environment of our institute show that the position error can be kept small enough to perform navigation tasks.

Space Robotics: Dynamics and Control

Abstract: Preface. 1. Kinematic Dynamic Properties of an Elbow Manipulator Mounted on a Satellite R.E. Lindberg, R.W. Longman, M.F. Zedd. 2. The Kinetics and Workspace of a Satellite-Mounted Robot R.W. Longman. 3. On the Dynamics of Space Manipulators Using the Virtual Manipulator, with Applications to Path Planning Z. Vafa, S. Dubowsky. 4. Dynamic Singularities in Free-Floating Space Manipulators E. Papadopoulos, S. Dubowsky. 5. Nonholonomic Motion Planning of Free-Flying Space Robots via a Bi-Directional Approach Y. Nakamura, R. Mukherjee. 6. Attitude Control of Space Platform/Manipulator System Using Internal Motion C. Fernandez, L. Gurvits, Zexiang Li. 7. Control of Space Manipulators with Generalized Jacobian Matrix K. Yoshida, Y. Umetani. 8. Sensory Feedback Control for Space Manipulators Y. Masutani, F. Miyazaki. 9. Adaptive Control of Space Robot System with an Attitude Control Base Yangsheng Xu, Heung-Yeung Shum, Ju-Jang Lee, T. Kanade. 10. Experiments in Autonomous Navigation and Control of a Multi-Manipulator, Free-Flying Space Robot M.A. Ulman, R.H. Cannon, Jr. Index.

Mobile work robot system

Abstract: The system includes a mobile work robot and a separate station. The mobile robot is equipped to perform prescribed tasks, such as cleaning building floors. The station is equipped to remotely control the movement of the mobile work robot and to perform maintenance on the mobile work robot, such as the replacement of parts as well as replenishment of consumable goods necessary for the mobile work robot to move and work. In addition, the cleaning means equipped on the station performs the cleaning and disinfection of the mobile work robot.

System and method for performing mobile robotic work operations

Abstract: A precise automated work system and method is provided One or more self-navigating robots can perform automated work operations with precision given six degrees of freedom in a undulating, sloping or irregular terrain, such as, a commercial truck garden A self-propelled robot moves through the garden and performs gardening tasks following a specified course by dead-reckoning and periodically determining its position and orientation by a navigation fix At least seven navigation beacons are positioned around a perimeter of a garden work area Each beacon emits electromagnetic radiation across the garden for detection by the self-propelled robot A panoramic image collector gathers and focuses electromagnetic radiation from each navigation beacon on an electronic camera to form at least seven beam spots The relative position of the detected beam spots in the focal plane vary depending upon the six degrees of freedom for robot movement in a garden: the robot's three-dimensional position (x,y,z) and the robot's orientation (heading, pitch, and roll) A navigation module determines the position and orientation of the robot within the garden based on the output of the imaging camera A self-propelled gardening robot performs many varied automated farming tasks from tillage, to planting, to harvesting by controlling the point of impact of a implement carried by a robot with precision, that is, to within an inch on average for any given position coordinate Commercial feasibility of small truck gardens is improved as automation is comprehensive and accessible to the solitary farmer

Constrained Cartesian motion control for teleoperated surgical robots

Abstract: This paper addresses the problem of optimal motion control for teleoperated surgical robots, which must maneuver in constrained workspaces, often through a narrow entry portal into the patient's body. The control problem is determining how best to use the available degrees of freedom of a surgical robot to accomplish a particular task, while respecting geometric constraints on the work volume, robot mechanism, and the specific task requirements. We present a method of formulating desired motions as sets of task goals in any number of coordinate frames (task frames) relevant to the task, optionally subject to additional linear constraints in each of the task frames. Mathematically, the kinematic control problem is posed as a constrained quadratic optimization problem and is shown to be computable in real time on a PC. We will present experimental results of the application of this control methodology to both kinematically deficient and kinematically redundant robots. Specifically, we will discuss the control issues within the context of a representative set of tasks in robot-assisted laparoscopy, which includes (but is not limited to) teleoperated navigation of a laparoscopic camera attached to a surgical robot. A system based on this control formalism has been used in preclinical in vivo studies at the Johns Hopkins University Medical Center and the early experience with the system will be summarized.

Learning Maps for Indoor Mobile Robot Navigation.

Abstract: : Autonomous robots must be able to learn and maintain models of their environments. Research on mobile robot navigation has produced two major paradigms for mapping indoor environments: grid-based and topological. While grid-based methods produce accurate metric maps, their complexity often prohibits efficient planning and problem solving in large-scale indoor environments. Topological maps, on the other hand, can be used much more efficiently, yet accurate and consistent topological maps are considerably difficult to learn in large-scale environments. This paper describes an approach that integrates both paradigms: grid-based and topological. Grid-based maps are learned using artificial neural networks and Bayesian integration. Topological maps are generated on top of the grid- based maps, by partitioning the latter into coherent regions. By combining both paradigms-grid-based and topological-, the approach presented here gains the best of both worlds: accuracy/consistency and efficiency. The paper gives results for autonomously operating a mobile robot equipped with sonar sensors in populated multi-room environments.

Observer-based supervision and fault detection in robots using nonlinear and fuzzy logic residual evaluation

Abstract: A high degree of automation in flexible production units require powerful tools for supervision and fault detection to maintain quality and productivity. In this paper, an observer-based fault detection method is proposed which makes use of non-measurable process information instead of installing as many sensors as possible. The detection method is reviewed and applied to the fault detection problem in an industrial robot, using a dynamic robot model. The robot model is enhanced by the inclusion of nonlinear friction terms. A new residual evaluation approach of model-based fault detection methods is investigated for processes which exhibit unstructured disturbances, arising from model simplification. The present analytical approaches are applicable only to structured approaches. In this paper a fuzzy-logic approach is presented which is capable to address unstructured disturbances as well. Finally, some practical results for an industrial robot example are presented.

Trajectory Tracking Control for Navigation of the Inverse Pendulum Type Self-Contained Mobile Robot

Abstract: In this paper, we discuss the trajectory control for a wheeled inverse pendulum type mobile robot. The robot has two independent driving wheels on the same axle, and a gyro type sensor to measure the inclination angular velocity of the body and rotary encoders to measure wheel rotation. The purpose of this work is to make a robot autonomously navigate in a plane while keeping its own balance. The control algorithm consists of three parts: balance and velocity control, steering control and straight line tracking control. We designed and implemented a vehicle command system for such robot to control using the proposed algorithm. Experiments of the navigation in a real indoor environment have been performed using our experimental robot “Yamabico Kurara”.

Skill acquisition from human demonstration using a hidden Markov model

Abstract: A new approach to skill acquisition in assembly is proposed. An assembly skill is represented by a hybrid dynamic system where a discrete event controller models the skill at the task level. The output of the discrete event controller provides the reference commands for the underlying robot controller. This structure is naturally encoded by a hidden Markov model (HMM). The HMM parameters are obtained by training on sensory data from human demonstrations of the skill. Currently, assembly tasks have to be performed by human operators or by robots using expensive fixtures. Our approach transfers the assembly skill from an expert human operator to the robot, thus making it possible for a robot to perform assembly tasks without the use of expensive fixtures.

Application of rubber artificial muscle manipulator as a rehabilitation robot

Abstract: The application of robot to rehabilitation has become a matter of great concern. This study deals with an exercise for restoration of function being one of important rehabilitation tasks. An exercise of single joint has already been achieved with some automatically controlled machines. Now, the multijoint exercise becomes desirable, which requires the exercise robot with multi ple degrees of freedom to generate more realistic motion pattern. This kind of robot has to be absolutely safe for humans. A pneumatic calculator may be so effective for such a robot because of the flexibility from air compressibility that a rubber artificial muscle manipulator pneumatically driven is applied to construct the exercise robot with two degrees of freedom. Also an impedance control strategy is employed to realize various exercise motion modes. Further, an identification method of the recovery condition is proposed to execute the effective rehabilitation. Some experiments show the availability of proposed rehabilitation robot system.