Showing papers on "Robot published in 1988"

The complexity of robot motion planning

Abstract: The Complexity of Robot Motion Planning makes original contributions both to robotics and to the analysis of algorithms. In this groundbreaking monograph John Canny resolves long-standing problems concerning the complexity of motion planning and, for the central problem of finding a collision free path for a jointed robot in the presence of obstacles, obtains exponential speedups over existing algorithms by applying high-powered new mathematical techniques.Canny's new algorithm for this "generalized movers' problem," the most-studied and basic robot motion planning problem, has a single exponential running time, and is polynomial for any given robot. The algorithm has an optimal running time exponent and is based on the notion of roadmaps - one-dimensional subsets of the robot's configuration space. In deriving the single exponential bound, Canny introduces and reveals the power of two tools that have not been previously used in geometric algorithms: the generalized (multivariable) resultant for a system of polynomials and Whitney's notion of stratified sets. He has also developed a novel representation of object orientation based on unnormalized quaternions which reduces the complexity of the algorithms and enhances their practical applicability.After dealing with the movers' problem, the book next attacks and derives several lower bounds on extensions of the problem: finding the shortest path among polyhedral obstacles, planning with velocity limits, and compliant motion planning with uncertainty. It introduces a clever technique, "path encoding," that allows a proof of NP-hardness for the first two problems and then shows that the general form of compliant motion planning, a problem that is the focus of a great deal of recent work in robotics, is non-deterministic exponential time hard. Canny proves this result using a highly original construction.John Canny received his doctorate from MIT And is an assistant professor in the Computer Science Division at the University of California, Berkeley. The Complexity of Robot Motion Planning is the winner of the 1987 ACM Doctoral Dissertation Award.

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.

A new technique for fully autonomous and efficient 3D robotics hand-eye calibration

Abstract: The authors describe a novel technique for computing position and orientation of a camera relative to the last joint of a robot manipulator in an eye-on-hand configuration. It takes only about 100+64N arithmetic operations to compute the hand/eye relationship after the robot finishes the movement, and incurs only additional 64 arithmetic operations for each additional station. The robot makes a series of automatically planned movements with a camera rigidly mounted at the gripper. At the end of each move, it takes a total of 90 ms to grab an image, extract image feature coordinates, and perform camera extrinsic calibration. After the robot finishes all the movements, it takes only a few milliseconds to do the calibration. A series of generic geometric properties or lemmas are presented, leading to the derivation of the final algorithms, which are aimed at simplicity, efficiency, and accuracy while giving ample geometric and algebraic insights. Critical factors influencing the accuracy are analyzed, and procedures for improving accuracy are introduced. Test results of both simulation and real experiments on an IBM Cartesian robot are reported and analyzed. >

Model-Based Control of a Robot Manipulator

Abstract: Model-Based Control of a Robot Manipulator presents the first integrated treatment of many of the most important recent developments in using detailed dynamic models of robots to improve their control. The authors' work on automatic identification of kinematic and dynamic parameters, feedforward position control, stability in force control, and trajectory learning has significant implications for improving performance in future robot systems. All of the main ideas discussed in this book have been validated by experiments on a direct-drive robot arm.The book addresses the issues of building accurate robot models and of applying them for high performance control. It first describes how three sets of models - the kinematic model of the links and the inertial models of the links and of rigid-body loads - can be obtained automatically using experimental data. These models are then incorporated into position control, single trajectory learning, and force control. The MIT Serial Link Direct Drive Arm, on which these models were developed and applied to control, is one of the few manipulators currently suitable for testing such concepts.Contents: Introduction. Direct Drive Arms. Kinematic Calibration. Estimation of Load Inertial Parameters. Estimation of Link Inertial Parameters. Feedforward and Computed Torque Control. Model-Based Robot Learning. Dynamic Stability Issues in Force Control. Kinematic Stability Issues in Force Control. Conclusion.Chae An is Research Staff Member, IBM T.J. Watson Research Center, Christopher Atkeson is an Assistant Professor and John Hollerbach is an Associate Professor in the MIT Department of Brain and Cognitive Sciences and the MIT Artificial Intelligence Laboratory. Model-Based Control of a Robot Manipulator is included in the Artificial Intelligence Series edited by Patrick Winston and Michael Brady.

Hierarchical neural network model for voluntary movement with application to robotics

Abstract: In order to control voluntary movements, the central nervous system must solve the following three computational problems at different levels: determination of a desired trajectory in the visual coordinates; transformation of the trajectory from visual coordinates to body coordinates; and generation of motor commands. Based on physiological information and previous models, computational theories are proposed for the first two problems, and a hierarchical neural network model is introduced to deal with motor commands. The application of this approach to robotics is outlined. >

Compliant robot motion II. A control approach based on external control loops

Abstract: A control approach for the execution of robot tasks in contact with the environment is worked out. The input to the con troller consists of the task specification described in part I. The control a...

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. >

Realization of robot motion based on a learning method

Abstract: To make a robot track a given desired motion trajectory, a learning control scheme is proposed which is based on the repeatability of robot motion. In this scheme the robot obtains a desired motion by repeating trials (test motion). A merit of this control scheme is that the input torque pattern that generates the desired motion can be formed without estimating the physical parameters of robot dynamics. In practice, to allow the robot motion to approach the desired one in each trial, the input torque given to the robot at the present trial is modified only by the velocity signal of the real robot motion at the previous trial and the desired one. The convergence to the desired motion is theoretically proved for a linear time-varying mechanical system, which is an approximate representation of nonlinear robot dynamics in the vicinity of the desired motion. The effectiveness of this control scheme is demonstrated through actual experiments in which a revolute-type manipulator with three degrees of freedom is used, and the desired motion trajectory is given not only in terms of joint-angle coordinates but also in terms of task-oriented coordinates. >

Dynamic multi-sensor data fusion system for intelligent robots

Abstract: The objective of the authors is to develop an intelligent robot workstation capable of integrating data from multiple sensors. The investigation is based on a Unimation PUMA 560 robot and various external sensors. These include overhead vision, eye-in-hand vision, proximity, tactile array, position, force/torque, cross-fire, overload, and slip-sensing devices. The efficient fusion of data from different sources will enable the machine to respond promptly in dealing with the 'real world'. Towards this goal, the general paradigm of a sensor data fusion system has been developed, and some simulation results, as well as results from the actual implementation of certain concepts of sensor data fusion, have been demonstrated. >

Optimal load distribution for two industrial robots handling a single object

Abstract: The load distribution problem for two coordinating industrial robots handling a single object is studied. When two industrial robots grasp a single object, the total number of degrees of freedom is usually greater than six. Thus, the joint torques of two robots for a required motion of the object is not unique. The redundant degrees of freedom may be used to optimize certain kind of performance. The least energy consumption is selected as the optimization criterion. Optimal algorithms without and with a bound on the joint torques are investigated. The results show that the algorithms are computationally complicated and not suitable for real-time applications. Alternatively, optimal algorithms are proposed for load distribution with minimum exerted forces on the object. These algorithms require less computational time, which makes them attractive for real-time applications. >

Uncertain geometry in robotics

Abstract: Robots must operate in an environment which is inherently uncertain This uncertainty is important in areas such as modeling, planning and the motion of manipulators and objects; areas where geometric analysis also plays an important part To operate efficiently, a robot system must be able to represent, account for, and reason about the effects of uncertainty in these geometries in a consistent manner We maintain that uncertainty should be represented as an intrinsic part of all geometric descriptions We develop a description of uncertain geometric features as families of parameterized functions together with a distribution function defined on the associated parameter vector We consider uncertain points, curves and surfaces, and show how they can be manipulated and transformed between coordinate frames in an efficient and consistent manner The effectiveness of these techniques is demonstrated by application to the problem of developing maximal information sensing strategies

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.

Approach to the dynamically reconfigurable robotic system

Abstract: In this paper, a newly proposed robotic system called the dynamically reconfigurable robotic system (DRRS), is reconfigurable for given tasks, so that the level of flexibility and adaptability is much higher for a change of working environments than conventional robots which have un-metamorphic shapes and structures. This robotic system consists of many cells which have fundamental mechanical functions. Each cell is able to detach and combine autonomously, so that the system can self-reorganize depending on a task or on working environments, and can also be self-repairing. DRRS has many applications in many fields, e.g. maintenance robots, more advanced working robots, free-flying service robots in space, more evolved flexible automation, etc. This paper shows the concept of this system, the mechanism of cells, the basic experimental results of the rough approach control between cells, and the decision method of such cell-structured manipulator configurations. This method is based on the reachability of the manipulators for working points, and so is able to apply the design of ordinary manipulators.

Device and method for correction of robot inaccuracy

Abstract: A method and device for improving orientation and/or location accuracy of a programmable robot with respect to a target object. The method consists of calibrating the position of a terminal control frame associated with a robot end-effector which is coupled to a robot distal link. Separated reference positions external from the robot are identified, as to geometry and spatial data. This identification data is stored for later recall and comparison for use in determining a localized relative frame of reference. The robot end-­effector is moved to a first reference position and a rigid body error correction is determined. This correction is stored in computer memory for application to later computer movement.

Solution to the inverse kinematics problem in robotics by neural networks

Abstract: The authors use a neural-network model in the solution of the inverse kinematics problem in robotics. It is found that the neural network can be trained to generate a fairly accurate solution which, when augmented with local differential inverse kinematic methods, results in minimal burden on processing load of each control cycle and thus allows real-time robot control. Further benefits are expected from the natural fault tolerance of the neural network and the elimination of the costly derivation and programming of the inverse kinematic algorithm. >

On the identification of the inertial parameters of robots

Abstract: An algorithm is presented for the identification of the inertial parameters and friction coefficients of robots. The algorithm is not required to measure or calculate the joint accelerations. The identification model is based on the energy theorem, is linear in the robot parameters, and is easy to calculate. An example of a two-degree-of-freedom robot is presented. >

Real time versatile robotics hand/eye calibration using 3D machine vision

Abstract: A technique is described for computing 3-D position and orientation of a camera relative to the last joint of a robot manipulator in an eye-on-hand configuration. The calibration can be done within a fraction of a millisecond after the robot finishes the movement. The setup is simple (a planar set of calibration points arbitrarily placed on the work table, in addition to robot and camera) and is the same as that for a common camera calibration. This method is claimed to be faster, simpler, and more accurate than any existing technique for hand/eye calibration. Generic geometric properties of lemmas are presented, leading to the derivation of the final algorithms, which are aimed at simplicity, efficiency, and accuracy while giving ample geometric and algebraic insights. Besides describing the technique, critical factors influencing the accuracy are analysed, and procedures for improving accuracy are introduced. Tests results of both simulation and real experiments on an IBM Cartesian robot are reported. >

Dynamic control of robots with joint elasticity

Abstract: Reference is made to the problem of controlling the dynamic behavior of robots with rigid links but in presence of joint elasticity. It is shown that use of the more general class of dynamic nonlinear state-feedback allows solving both the feedback linearization and the input-output decoupling problems. A constructive procedure for the decoupling and linearizing feedback is given which is based on generalization system inversion and on the properties of the so-called zero-dynamics of the system. A case study of a planar two-link robot with elastic joints is included. The role of dynamic feedback for this class of robots is discussed. >

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. >

Three-dimensional vision structure for robot applications

Abstract: Focuses on the structure of robot sensing systems and the techniques for measuring and preprocessing 3-D data. To get the information required for controlling a given robot function, the sensing of 3-D objects is divided into four basic steps: transduction of relevant object properties (primarily geometric and photometric) into a signal; preprocessing the signal to improve it; extracting 3-D object features; and interpreting them. Each of these steps usually may be executed by several alternative techniques (tools). Tools for the transduction of 3-D data and data preprocessing are surveyed. The performance of each tool depends on the specific vision task and its environmental conditions, both of which are variable. Such a system includes so-called tool-boxes, one box for each sensing step, and a supervisor, which controls iterative sensing feedback loops and consists of a rule-based program generator and a program execution controller. Sensing step sequences and tools are illustrated for two 3-D vision applications at SRI International Company: visually guided robot arc welding and locating identical parts in a bin. >

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.

Design and test of a computer-stabilized unicycle

Abstract: This research investigates the stabilization of a one wheeled vehicle by means of active feedback control. The control methods of a human riding a unicycle are investigated first and a dynamic model which closely emulates the process is derived. A one wheeled robot with mass and inertia propeties similar to those of a young child was constructed and used as an experimental vehicle for testing various control algorithms. The research addresses aspects in the fields of robotics, artificial intelligence and modern digital control, but rather than specializing in any of these fields, it strives to combine these disciplines in a unique application where the interaction of these fields can be studied. An underlying approach of this research was to not only design but also evaluate control system performance in a laboratory environment without incurring large financial expenses. The robot has all its electrical and computational power on board, with the ability to receive commands from a radio transmitter to change its direction and forward speed. A linearized model was derived and optimal control systems to stabilize the vehicle were designed and simulated. An investigation into using accelerometers for detection of the deviation from vertical by measuring the specific force on the robot frame, was conducted. We found that this resulted in unacceptable closed loop system robustness. Theoretical and physical explanations for this phenomenon are presented as well as experimental results to confirm the extreme sensitivity of the design to these sensors. We show that accurate sensor information on the unicycle's orientation with respect to vertical facilitates the design of closed loop control systems with good stability and robustness characteristics. Such a control system for the longitudinal dynamics of the unicycle robot was demonstrated experimentally. The sensing, actuation and control abilities of a person riding a unicycle are compared with those of a computerized robot performing a similar task. We propose that this research and the test vehicle form the basis for theoretical and experimental studies into the application of nonlinear, robust and adaptive control systems techniques for unstable systems.

A multistage-approach to the dynamics and control of elastic robots

Abstract: The control of an elastic robot along a reference trajectory is performed in several steps. An optimal reference path for a rigid robot is generated, taking into account any restrictions and arbitrary robot/trajectory configurations. Tracking of that path is improved by regarding the elastic influences of all links and joints. For the purpose the robot is modeled as an elastic multibody system. A control scheme is added which feeds back strain-gauge measurements at the elastic arms to damp remaining oscillations. These three stages together allow high performance control of an elastic robot, which is proven by measurements at a three-degree-of-freedom laboratory robot. >

Redundant robot control using task based performance measures

Abstract: The joint velocities required to move the end-effector of a redundant robot with a desired linear and angular velocity depend on its configuration. Similarly, the joint torques produced due to the force and moment at the end-effector also depend on its configuration. When the robot is near a singular configuration, the joint velocities required to attain the end-effector velocity in certain directions are extremely high. Similarly, in some configurations the joint torque produced at certain joints may be high for a relatively small magnitude of external force. An infinite number of trajectories in the joint space can be used to achieve a desired end-effector trajectory for redundant robots. However, a joint trajectory resulting in robot configurations requiring lower joint velocities or joint torques is desired. This may be achieved through a proper utilization of redundancy. Local performance measures for redundant robots are defined in this article as indicators of their ability to follow a desired end-effector trajectory and their ability to apply desired forces at the end-effector. Thus, these performance measures depend on the task to be performed. Control algorithms which can be efficiently applied to redundant robots to improve these performance measures are presented. These control algorithms are based on the gradient projection method. Gradients of the performance measures used in the control schemes result in simple symbolic expressions for “real world” robots'. Feasibility and effectiveness of these control schemes is demonstrated through the simulation of a seven-degree-of-freedom redundant robot derived from the PUMA geometry.