R-3 Repository :: Browsing by Author "Walker, Ian D."

Browsing by Author "Walker, Ian D."

Now showing 1 - 20 of 50

A new method for solving the kinematics of multifingered grasping and general redundant manipulators: A task oriented approach
(1991) Chen, Yu-Che; Cheatham, John B., Jr.; Walker, Ian D.
Beside our arms, it is our hands that help us to perform tasks. At first glance, we seems to move our arms and use our hands naturally. On closer inspection, however, we find that both our arms and hands are redundant mechanisms which explains why our arms can approach an object using different postures and our hands can grasp the object with many feasible grasp configurations. Duplicating this phenomenon has led to many innovative designs of redundant arms as well as multifingered hands, and has sparked many useful analyses of these topics. This thesis presents a new approach to intelligent multifingered grasping and redundant arm manipulation. Methods proposed in this research yield a computationally efficient and physically meaningful model for the planning of grasp positions, the determination of squeezing finger forces and the visualization of the motions of redundant arms. Principles and concepts embedded in this analysis will help researchers to gain new insights toward better designs for hands and arms. The model developed in this thesis also provides mathematical justification for some of the motions of human arms and fingers. The main thrust of this analysis of multifingered grasping is the use of mechanical equivalent force/moment systems. These systems allow us to decompose each finger force into a normal and a tangential component. Using this decomposition of finger forces, we can visualize the contribution of each finger force by the resultant force and moment required to manipulate a grasped object. Additionally, the nature of this decomposition, which is one of the unique feature of our method, will allow intelligent utilization of touch sensors. The frictional constraints and the squeezing internal finger forces are elegantly taken into account through a computationally efficient algorithm for choosing grasp points. Our methods have also been extended into the grasp of solid objects. The second part of this thesis provides an efficient method for analyzing the inverse kinematic problem of redundant manipulators. Our method is based on fully using the directional properties of the columns of the Jacobian matrix which relates the joint velocities of the arm and the end effector velocities. Motions of a redundant manipulator are analyzed through its upper arm's motion and wrist's motion and the Jacobian matrix is partitioned accordingly. It is shown that the motion of the upper arm and the wrist can be evaluated separately and in parallel though this vectorized approach.
Adaptive Fault Detection and Tolerance for Robots
(TSI Press, 1994-08-01) Visinsky, Monica L.; Cavallaro, Joseph R.; Walker, Ian D.; Center for Multimedia Communication
In existing robot fault detection schemes, sensed values of the joint status (position, velocity, etc.) are typically compared against expected or desired values, and if a given threshold is exceeded, a fault is inferred. The thresholds tend to be empirically determined and held constant over a wide range of trajectories. This leads to false alarms when the threshold is too small to counter the error-inducing effects model inaccuracy and to undetected faults when the threshold is too large for the given situation. This paper presents new methods for adaptively choosing fault detection thresholds, subject to sensing and modeling inaccuracies and the changing status of the robot. Our approach chooses optimal thresholds based on a Singular Value Decomposition (SVD) of a specialized error regressor format of the dynamics to minimize the possibility of false alarms or undtected failures. The thresholds vary dynamically with the changing trajectory and configuration of the robot and with the robot's failure status. Examples of the fault detection scheme for a non-planar 3 DOF robot are given.
Alignment of threaded parts using a robot hand: Theory and experiments
(1998) Diftler, Myron Arthur; Walker, Ian D.
Techniques for determining and correcting threaded part alignment using minimal force and angular position data are developed to augment currently limited techniques for aligning threaded parts. These new techniques are based on backspinning a nut with respect to a bolt and measuring the force change that occurs when the bolt "drops" into the nut. Kinematic models that describe the relationship between threaded parts during backspinning are presented and are used to show how angular alignment may be determined. The models indicate how to distinguish between the aligned and misaligned cases of a bolt and a nut connection by using axial force data only. In addition, by tracking the in-plane relative attitude of the bolt during spinning, data can be obtained on the direction of the angular misalignment which, in turn, is used to correct the misalignment. Experiments using a three fingered Stanford/JPL robotic hand validate portions of the derived kinematic models while a higher resolution fixture provides additional data. Evaluation of the correlation between the test data and the kinematic models lead to strategies for identifying and correcting misalignment. One technique that tracks the inplane attitude when a drop occurs at moderate to large misalignments is evaluated as an improvement to the existing techniques for automated alignment of threaded fasteners.
Analysis of Robots for Hazardous Environments
(IEEE, 1997-01-01) Harpel, Barbara McLaughlin; Dugan, Joanne Bechta; Walker, Ian D.; Cavallaro, Joseph R.; Center for Multimedia Communication
Reliability analysis of fault tolerant systems often ignores the small probability that a failure might not be detected or, if detected, may not be properly handled. The probability that the failure is detected and properly handled is called coverage. Inclusion of coverage in reliability analysis is especially important when analyzing critical systems, systems which for some reason are not easily reparable, or systems whose failure can result in serious damage to the system or its surroundings. One example of a system which can cause such damage is a robot manipulator arm. Robots are being increasingly employed in remote and hazardous environments such as in space and in nuclear waste cleanup, and can exhibit a wild response to subsystem failure, damaging themselves and/or their surroundings. Addition of redundancy to such systems can increase their reliability by allowing continued operation in the presence of faults (provided that the fault is covered), an advantage in a system where repair is difficult or impossible. Coverage models have been used to analyze the behavior of fault-tolerant computer systems in the presence of faults, providing an estimate of the relative probability of an uncovered vs. a covered component failure (given that a fault has occurred) [1]. This paper extends the use of coverage models to the basic components of the joint of a robot and presents data utilizing the calculated coverage for a three-joint robot manipulator arm designed to operate in the plane.
Application of optimal damped least-squares method to inverse kinematics of robotic manipulators
(1991) Deo, Arati Suresh; Walker, Ian D.
Inverse kinematics for redundant robotic manipulators is typically computed using the pseudoinverse of the manipulator Jacobian. Though the pseudoinverse yields the most accurate minimum-norm joint velocity vector, it fails to prevent high joint velocities when the manipulator is in the neighborhood of singularities. The Singularity Robust Inverse (SRI), which arises from the Damped Least-Squares technique proves to be a better inverse kinematic solution than the pseudoinverse near singular configurations. The SRI computes damped joint velocities but causes some deviation of the end-effector from its planned trajectory. The SRI performs most satisfactorily when the damping factor, which represents the trade-off between the accuracy and feasibility of the computed solution is calculated optimally, i.e. it yields minimum deviation of the end-effector while ensuring the feasibility of the joint velocities at all points in the manipulator workspace. This work introduces a new method of computing the optimal damping factor. The SRI can also be used to optimize another sub-task criterion in addition to performing the main motion task and avoiding high joint velocities at singularities.
Control methods for rigid and flexible kinematically redundant robot manipulators
(1991) Nguyen, Luong An; de Figueiredo, Rui J. P.; Walker, Ian D.
In the coming era of the Space Station Freedom, many robotic manipulators will be working simultaneously on various parts of the space station structure. Since each link of a manipulator is a moving body relative to other bodies, they form a tree structure of interconnected bodies. Undoutedly, many of these manipulators will possess certain degree of flexibility, at links as well as at joints. To describe accurately the dynamics of such a system in a generic way, is certainly not a trivial task. However, if we approximate each flexible link as a long slender beam and assume that flexible joints behave like torsional springs, a scalar set of equations of motion can be derived explicitly for use in real time simulation or control applications. Kinematic redundancy of manipulators has been used in control algorithms to avoid singularities, evade obstacles, minimize joint torques, manipulator kinetic energy, end effector contact forces, etc ... All of these approaches have been associated with rigid manipulators where there are no unpredictable flexible motions. When dealing with flexible manipulators, the flexibility of the system will cause undesired inaccuracy in end effector motion. However, if these manipulators are kinematically redundant, we show in this thesis that their kinematic redundancy can be used to compensate for the end effector motion inaccuracy and in many cases help damp out the vibrations. Based on our newly developed dynamic model of a system of multiple space-based flexible manipulators, control algorithms are designed to regulate the flexibility while maintaining precise tracking of the end effector trajectory. These control algorithms can either utilize a manipulator kinematic redundancy to control its flexibility or borrow other arms' motion to accomplish the same task provided that the arms are interconnected. Kinematic redundancy is also useful in optimizing the robustness of controllers. Given a manipulator's characteristics, parameter uncertainties, desired trajectories and controller design, it can be shown that under certain conditions, the tracking errors in end effector space are L$\sb\infty$ bounded. If the manipulator is kinematically redundant, we show how its redundancy can be used to minimize these tracking error bounds and in some cases, stabilize an unstable system.
Dynamic Fault Reconfigurable Intelligent Control Architectures for Robotics
(American Nuclear Society, 1993-04-01) Cavallaro, Joseph R.; Walker, Ian D.; Center for Multimedia Communication
In this paper we describe new progress in our development of an Intelligent Control Framework for robots which dynamically reconfigures itself to cope with faults in either sensors or joint hardware. The Framework is configured to allow the incorporation of new approaches for on-line critiquing of user plans and commands within the framework. We discuss integration of the two components above to produce an Intelligent Robot Operating System which can tolerate failures or unexpected actions from both the logical (user) world and the physical (manipulator) world and continue operation where possible.
A Dynamic Fault Tolerance Framework for Remote Robots
(IEEE, 1995-08-01) Visinsky, Monica L.; Cavallaro, Joseph R.; Walker, Ian D.; Center for Multimedia Communication
Fault tolerance is increasingly important for robots, especially those in remote or hazardous environments. Robots need the ability to effectively detect and tolerate internal failures in order to continue performing their tasks without the need for immediate human intervention. This paper presents a layered fault tolerance framework containing new fault detection and tolerance schemes. The framework is divided into servo, interface, and supervisor layers. The servo layer is the continuous robot system and its normal controller. The interface layer monitors the servo layer for sensor or motor failures using analytical redundancy based fault detection tests. A newly developed algorithm generates the dynamic thresholds necessary to adapt the detection tests to the modeling inaccuracies present in robotic control. Depending on the initial conditions, the interface layer can provide some sensor fault tolerance automatically without direction from the supervisor. If the interface runs out of alternatives, the discrete event supervisor searches for remaining tolerance options and initiates the appropriate action based on the current robot structure indicated by the fault tree database. The layers form a hierarchy of fault tolerance which provide different levels of detection and tolerance capabilities for structurally diverse robots.
Dynamic Senor-Based Fault Detection for Robots
(SPIE - The International Society for Optical Engineering, 1993-09-01) Visinsky, Monica L.; Cavallaro, Joseph R.; Walker, Ian D.; Center for Multimedia Communication
Fault detection and fault tolerance are increasingly important for robots in space or hazardous environments due to the dangerous and often inaccessible nature of these environs. We have previously developed algorithms to enable robots to autonomously cope with failures or critical sensors and motors. Typically, the detection thresholds used in such algorithms to mask out model and sensor errors are empirically determined and are based on a specific robot trajectory. We have noted, however, that the effect of model and sensor inaccuracy fluctuates dynamically as the robot and as failures occur. The thresholds, therefore, need to be more dynamic and respond to the changes in the robot system so as to maintain an optimal bound for sensing real failures in the system versus misalignment due to modeling errors. In this paper, we analyze the Reachable Measurement Intervals method of computing dynamic thresholds and explore its applicability to robotic fault detection.
Effectiveness and performance analysis of a class of parallel robot controllers with fault tolerance
(1996) Hamilton, Deirdre Lynne; Walker, Ian D.; Bennett, John K.
In the past, robots were only applied to simple repetitive tasks, such as assembly line work. However robotics research now encompasses a broad spectrum of application possibilities. Robots are being considered for use in more advanced manufacturing applications, medical and space applications, and numerous other tasks. Speed and precision of control are two primary issues for current and future applications of robotic systems. Fault tolerance is also increasingly important for many robot tasks. This work focuses on improving the efficiency and fault tolerance capabilities of robot controllers. Here we address the following questions: "How can robot control be improved from the perspective of the algorithm implementation? What combination of speed and precision can we achieve for good overall performance?" Due to the coupling in the dynamics equations, coarse-grain parallelization of robot control algorithms is particularly difficult. In this thesis, we develop a new parallel control algorithm for robots based on the Newton-Euler dynamics formulation that overcomes the serial nature of these equations, allowing a high level of parallelism. Our controller uses data from a previous control step in current calculations to allow many more tasks to be executed in parallel, thus providing higher control update rates. The use of 'stale' data is an effective solution to the speedup problem, but presents some special difficulties. A stability issue when using 'stale' data that is encountered in previous algorithm approaches is discussed here. The incorporation of fault tolerance techniques into robot systems improves the reliability, but also increases the hardware and computational requirements in the overall system. Since all of these things affect system design, it is not always clear how to evaluate the merit, or 'effectiveness' of different fault tolerance approaches for a given application. In this thesis, we present a new set of performance criteria designed to measure and compare the effectiveness of robot fault tolerance strategies. The measures, which are designed to evaluate fault tolerance/performance/cost tradeoffs, can also be used to evaluate pure performance or pure fault tolerance strategies. We show their usefulness using a variety of proposed fault tolerance approaches in the literature, focusing on multiprocessor control architectures.
Evaluating the reliability of prototype degradable systems
(Elsevier Science Ltd, 2001-04-01) Leuschen, Martin L.; Walker, Ian D.; Cavallaro, Joseph R.; Center for Multimedia Communication
The technique introduced in this paper is a new technique for analyzing fault tolerant designs under considerable uncertainty, such as seen in unique or few-of-a-kind devices in poorly known environments or pre-prototype design analyses. This technique is able to provide useful information while maintaining the uncertainty inherent in the original specifications. The technique introduced here is a logical extension of the underlying concepts of fuzzy sets and Markov models. Although originally developed for robotic systems, the technique is more broadly applicable. This paper develops fuzzy Markov modeling and uses it to analyze a specific robot designed for hazardous waste removal and specific types of electronic systems.
Experimental AR Fault Detection Methods for a Hydraulic Robot
(ISSC, 2000-09-01) Leuschen, Martin L.; Walker, Ian D.; Cavallaro, Joseph R.; Gamache, Ronald; Martin, Mike; Center for Multimedia Communication
This paper focuses on practical use and theoretical elaboration of the analytical redundancy technique which is used to efficiently detect faults that have been determined to be mission-hazardous by previous FMECA and fault tree analyses of the Rosie system. We believe we have contributed significant improvements to the potential overall reliability of the system. Additionally, we have expanded the applicability of the AR method to nonlinear systems in the course of our work, making this valuable fault detection method more broadly applicable.
Expert System Framework for Fault Detection and Fault Tolerance in Robotics
(ASME, 1992-11-01) Visinsky, Monica L.; Cavallaro, Joseph R.; Walker, Ian D.; Center for Multimedia Communication
Fault tolerance is of increasing importance for modern autonomous industrial robots. The ability to detect and tolerate failures will enable robots to effectively cope with internal failures and continue performing assigned tasks without the need for immediate human intervention. To monitor fault tolerance actions performed by lower level routines and to provide higher level information about a robot's recovery capabilities, we use an expert system to develop a novel fault tolerance framework combining fault detection and tolerance routines with dynamic fault tree analysis. Fault tree analysis reveals the key components for providing fault detection and tolerance within a system. The trees can also be used quantitatively to provide a dynamic estimate of the probability of failure of the entire system or various subsystems. Using fault trees as a standard framework, the expert system package can provide fault tolerance for robots of significantly different origin and structure.
Expert System Framework for Fault Detection and Fault Tolerance in Robotics
(Elsevier Science Ltd, 1994-01-01) Visinsky, Monica L.; Cavallaro, Joseph R.; Walker, Ian D.; Center for Multimedia Communication
Fault tolerance is of increasing importance for modern robots. The ability to detect and tolerate failures enables robots to effectively cope with internal failures and continue performing assigned tasks without the need for immediate human intervention. To monitor fault tolerance actions performed by lower level routines and to provide higher level information about a robot's recovery capabilities, we present an expert system and critic which together form a novel and intelligent fault tolerance framework integrating fault detection and tolerance routines with dynamic fault tree analysis. A higher level, operating system inspired critic layer provides a buffer between robot fault tolerant operations and the user. The expert system gives the framework the modularity and flexibility to quickly convert between a variety of robot structures and tasks. It also provides a standard interface to the fault detection and tolerance software and a more intelligent means of monitoring the progress of failure and recovery throughout the robot system. The expert system further allows for prioritization of tasks so that the components essential to fault detection and tolerance within a system and detail the interconnection between failures in the system. The trees are also used quantitatively to provide a dynamic estimate of the probability of failure of the entire system or various subsystems.
Failure Mode Analysis for a Hazardous Waste Clean-up Manipulator
(Elsevier Science Limited, 1996-05-01) Walker, Ian D.; Cavallaro, Joseph R.; Center for Multimedia Communication
This paper describes the application of Fault Tree Analysis to the design phase of a robot manipulator for hazardous waste retrieval. The robot is to be deployed in single-shell under-ground storage tanks at the US Department of Energy (DOE) site in Hanford, Washington. These tanks contain a variety of highly radioactive waste types, necessitating extremely safe and reliable manipulator operation. Based on preliminary design drawings of this long-reach manipulator, fault trees were constructed for several critical failure scenarios. Analysis of the trees revealed a number of ways to improve the safety and reliability of the manipulator design. This paper presents a summary of the fault tree analysis, with a discussion of the applicability of qualitative and quantitative fault tree methods to hazardous waste robotics.
Failure Mode Analysis of a Proposed Manipulator-based Hazardous Material Retrieval System
(American Nuclear Society, 1997-04-01) Cavallaro, Joseph R.; Walker, Ian D.; Center for Multimedia Communication
Failure mode and reliability analysis is particularly important for robot manipulators to be deployed in remote environments, where inspection and repair are diffcult, and reliability is of prime importance. This is particularly true for manipulators involved in hazardous waste management operations, where failure could be both expensive and highly dangerous. In this paper, we describe a Fault Tree Analysis and detailing of the major failure modes of a robot manipulator-based system for tank waste retrieval. The advantages and limitations of this type of analysis for hazardous waste robotics are detailed and discussed.
Fault Detection and Fault Tolerance in Robotics
(1991-07-01) Visinsky, Monica L.; Walker, Ian D.; Cavallaro, Joseph R.; Center for Multimedia Communication
Robots are used in inaccessible or hazardous environments in order to alleviate some of the time, cost and risk involved in preparing men to endure these conditions. In order to perform their expected tasks, the robots are often quite complex, thus increasing their potential for failures. If men must be sent into these environments to repair each component failure in the robot, the advantages of using the robot are quickly lost. Fault tolerant robots are needed which can effectively cope with failures and continue their tasks until repairs can be realistically scheduled. Before fault tolerant capabilities can be created, methods of detecting and pinpointing failures must be perfected. This paper develops a basic fault tree analysis of a robot in order to obtain a better understanding of where failures can occur and how they contribute to other failures in the robot. The resulting failure flow chart can also be used to analyze the resiliency of the robot in the presence of specific faults. By simulating robot failures and fault detection schemes, the problems involved in detecting failures for robots are explored in more depth. Future work will extend the analyses done in this paper to enhance Trick, a robotic simulation testbed, with fault tolerant capabilities in an expert system package.
Fault detection and fault tolerance methods for robotics
(1992) Visinsky, Monica Lynn; Cavallaro, Joseph R.; Walker, Ian D.
Fault tolerance is increasingly important in modern autonomous or industrial robots. The ability to detect and tolerate failures allows robots to effectively cope with internal failures and continue performing designated tasks without the need for immediate human intervention. To support these fault tolerant capabilities, methods of detecting and isolating failures must be perfected. This thesis presents new fault detection algorithms which detect failures in robot components using analytical redundancy relations. The robot components critical to fault detection are revealed using an extended fault tree analysis. The thesis validates the algorithms using a simulated robot failure testbed. An intelligent fault tolerance framework is proposed in which a fault tree database and the detection algorithms work together to detect and tolerate sensor or motor failures in a robot system. Future work will expand the detection and tolerance routines and embed the framework into a more flexible expert system package.
Fault Residual Generation via Nonlinear Analytical Redundancy
(IEEE, 2005-05-01) Leuschen, Martin L.; Walker, Ian D.; Cavallaro, Joseph R.; Center for Multimedia Communication
Fault detection is critical in many applications, and analytical redundancy (AR) has been the key underlying tool for many approaches to fault detection. However, the conventional AR approach is formally limited to linear systems. In this brief, we exploit the structure of nonlinear geometric control theory to derive a new nonlinear analytical redundancy (NLAR) framework. The NLAR technique is applicable to affine systems and is seen to be a natural extension of linear AR. The NLAR structure introduced in this brief is tailored toward practical applications. Via an example of robot fault detection, we show the considerable improvement in performance generated by the approach compared with the traditional linear AR approach.
Fault Tolerant Algorithms and Architectures for Robotics
(IEEE, 1994-04-01) Hamilton, D.L.; Visinsky, Monica L.; Bennett, J.K.; Cavallaro, Joseph R.; Walker, Ian D.; Center for Multimedia Communication
As robot tasks in space, nuclear, and medical environments become more widespread, the issues of reliability and safety for robots are becoming more critical. Attempts to address these issues have resulted in a a recent surge of activity in robot fault tolerance. We concentrate on fault tolerance in the robot controller, and highlight the importance and potential of multiprocessor control architectures from the fault tolerance perspective. The issue of performance versus reliability is discussed. This paper also summarizes other work by our group at Rice University in the area of fault tolerance for robotics.

Browsing by Author "Walker, Ian D."

Results Per Page

Sort Options