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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Control framework for hand-arm coordination

Coordination of multiple manipulators requires cooperation at several levels in the control hierarchy. A distributed processing environment with no hardware dependencies except at the motor servo level would provide a flexible architecture for coordination. A system on these lines is being built to control an articulated hand and an arm. The four levels of control envisaged include a task decomposition level, a planning level, a scheduling level, and a server level. The hand will carry both force and tactile sensors, feedback from these are used to provide adaptive control in grasping tasks. The processing of the sensory information is performed by independent processes, with analyzed information being sent to the relevant layer of the system. The manipulators are also controlled by individual processes. All process can open communications with an active process sending commands or data, or receiving them. The scope of the system and the current setup are described along with future lines of development.

Agrawal, Sanjay↗
NASA NTRS1987

Control strategy for a dual-arm maneuverable space robot

A simple strategy for the attitude control and arm coordination of a maneuverable space robot with dual arms is proposed. The basic task for the robot consists of the placement of marked rigid solid objects with specified pairs of gripping points and a specified direction of approach for gripping. The strategy consists of three phases each of which involves only elementary rotational and translational collision-free maneuvers of the robot body. Control laws for these elementary maneuvers are derived by using a body-referenced dynamic model of the dual-arm robot.

Wang, P. K. C.↗
NASA NTRS1980

Control of a flexible robot arm

Exact equations of motion of an arm with known parameters were developed and analyzed preparatory to designing control systems for robotic manipulators. The design of an experimental one-link arm for testing control designs is presented.

Schmitz, E.↗
NASA NTRS1987

Nonlinear feedback control of multiple robot arms

Multiple coordinated robot arms are modeled by considering the arms: (1) as closed kinematic chains, and (2) as a force constrained mechanical system working on the same object simultaneously. In both formulations a new dynamic control method is discussed. It is based on a feedback linearization and simultaneous output decoupling technique. Applying a nonlinear feedback and a nonlinear coordinate transformation, the complicated model of the multiple robot arms in either formulation is converted into a linear and output decoupled system. The linear system control theory and optimal control theory are used to design robust controllers in the task space. The first formulation has the advantage of automatically handling the coordination and load distribution among the robot arms. In the second formulation, by choosing a general output equation, researchers can superimpose the position and velocity error feedback with the force-torque error feedback in the task space simultaneously.

Tarn, T. J.↗
NASA NTRS1997

Applying Space Technology to Enhance Control of an Artificial Arm

At the present time, myoelectric prostheses perform only one function of the hand: open and close with the thumb, index and middle finger coming together to grasp various shaped objects. To better understand the limitations of the current single-function prostheses and the needs of the individuals who use them, The Institute for Rehabilitation and Research (TIRR), sponsored by the National Institutes of Health (August 1992 - November 1994), surveyed approximately 2500 individuals with upper limb loss. When asked to identify specific features of their current electric prosthesis that needed improvement, the survey respondents overwhelmingly identified the lack of wrist and finger movement as well as poor control capability. Simply building a mechanism with individual finger and wrist motion is not enough. Individuals with upper limb loss tend to reject prostheses that require continuous visual monitoring and concentration to control. Robotics researchers at NASA's Johnson Space Center (JSC) and Rice University have made substantial progress in myoelectric teleoperation. A myoelectric teleoperation system translates signals generated by an able-bodied robot operator's muscles during hand motions into commands that drive a robot's hand through identical motions. Farry's early work in myoelectric teleoperation used variations over time in the myoelectric spectrum as inputs to neural networks to discriminate grasp types and thumb motions. The resulting schemes yielded up to 93% correct classification on thumb motions. More recently, Fernandez achieved 100% correct non-realtime classification of thumb abduction, extension, and flexion on the same myoelectric data. Fernandez used genetic programming to develop functions that discriminate between thumb motions using myoelectric signal parameters. Genetic programming (GP) is an evolutionary programming method where the computer can modify the discriminating functions' form to improve its performance, not just adjust numerical coefficients or weights. Although the function development may require much computational time and many training cases, the resulting discrimination functions can run in realtime on modest computers. These results suggest that myoelectric signals might be a feasible teleoperation medium, allowing an operator to use his or her own hand and arm as a master to intuitively control an anthropomorphic robot in a remote location such as outer space.

Atkins, Diane↗
NASA NTRS1993

Neural self-tuning adaptive control of non-minimum phase system

The motivation of this research came about when a neural network direct adaptive control scheme was applied to control the tip position of a flexible robotic arm. Satisfactory control performance was not attainable due to the inherent non-minimum phase characteristics of the flexible robotic arm tip. Most of the existing neural network control algorithms are based on the direct method and exhibit very high sensitivity, if not unstable, closed-loop behavior. Therefore, a neural self-tuning control (NSTC) algorithm is developed and applied to this problem and showed promising results. Simulation results of the NSTC scheme and the conventional self-tuning (STR) control scheme are used to examine performance factors such as control tracking mean square error, estimation mean square error, transient response, and steady state response.

Ho, Long T.↗
NASA NTRS1987

Coordination of multiple robot arms

Kinematic resolved-rate control from one robot arm is extended to the coordinated control of multiple robot arms in the movement of an object. The structure supports the general movement of one axis system (moving reference frame) with respect to another axis system (control reference frame) by one or more robot arms. The grippers of the robot arms do not have to be parallel or at any pre-disposed positions on the object. For multiarm control, the operator chooses the same moving and control reference frames for each of the robot arms. Consequently, each arm then moves as though it were carrying out the commanded motions by itself.

Barker, L. K.↗
NASA NTRS1994

Telepresence control of a dual-arm dexterous robot

Telepresence is an approach to teleoperation that provides egocentric, intuitive interactions between an operator and a remote environment. This approach takes advantage of the natural cognitive and sensory-motor skills of an on-orbit crew and effectively transfers them to a slave robot. A dual-arm dexterous robot operating under telepresence control has been developed and is being evaluated. Preliminary evaluation revealed several important observations that suggest the directions of future enhancement.

Li, Larry↗
NASA NTRS1985

Robust torque control of an elastic robotic arm based on invertibility and feedback stabilization

An approach to the control of elastic robotic systems for space applications using inversion, servocompensation, and feedback stabilization is presented. For simplicity, a robot arm (PUMA-type) with three rotational joints is considered. The third link is assumed to be elastic. Using an inversion algorithm, a nonlinear decoupling control law, u sub d, is derived such that in the closed loop system, independent control of joint angles by the three joint torquers is accomplished. For the stabilization of elastic oscillations, a linear feedback torquer control law, u sub s, is obtained applying linear quadratic optimization to the linearized arm model augmented with a servocompensator about the terminal state. Simulation results show that, in spite of uncertainties in the payload and vehicle angular velocity, good joint angle control and damping of elastic oscillations are obtained with the torquer control law u = u sub d + u sub s.

Singh, S. N.↗
NASA NTRS1975

Application of a postulate based control theory for an artificial arm

The biocontroller, remnant of the natural arm, and feedback elements must be considered in designing a controller for an above elbow artificial arm for amputees. This fundamental postulate is used to derive equations for developing the controller, which is shown in block diagrams.

Jacobsen, S. C.↗
NASA NTRS1994

Controlling under-actuated robot arms using a high speed dynamics process

The invention controls an under-actuated manipulator by first obtaining predetermined active joint accelerations of the active joints and the passive joint friction forces of the passive joints, then computing articulated body qualities for each of the joints from the current positions of the links, and finally computing from the articulated body qualities and from the active joint accelerations and the passive joint forces, active joint forces of the active joints. Ultimately, the invention transmits servo commands to the active joint forces thus computed to the respective ones of the joint servos. The computation of the active joint forces is accomplished using a recursive dynamics algorithm. In this computation, an inward recursion is first carried out for each link, beginning with the outermost link in order to compute the residual link force of each link from the active joint acceleration if the corresponding joint is active, or from the known passive joint force if the corresponding joint is passive. Then, an outward recursion is carried out for each link in which the active joint force is computed from the residual link force if the corresponding joint is active or the passive joint acceleration is computed from the residual link force if the corresponding joint is passive.

Jain, Abhinandan↗
DOE OSTI2026

X-Band Scanning ARM Precipitation Radar, CF/Radial Formatted, Quality Controlled

The X-band Scanning ARM Precipitation Radar (X-SAPR) is an X-band dual-polarization Doppler weather radar. The X-SAPR operates in a simultaneous transmit and receive (STAR) mode, meaning that the transmit signal is split so that power is transmitted on both horizontal and vertical polarizations at the same time. The X-SAPR transmitter is a 200 kW (peak power) magnetron. The receiver is based upon the Vaisala RVP-900 and runs Vaisala’s IRIS software. In addition to the first three Doppler moments (reflectivity, radial velocity, and spectra width), the X-SAPR also provides differential reflectivity, correlation coefficient, and specific differential phases. The dual-polarization variables enable estimates of rainfall rates and identification of precipitation types. At the Southern Great Plains site, three X-SAPRs surround the Central Facility, allowing the use of multi-Doppler velocity retrievals to estimate wind fields.

xsaprcfrqc↗
NASA NTRS1990

The Jet Propulsion Laboratory shared control architecture and implementation

A hardware and software environment for shared control of telerobot task execution has been implemented. Modes of task execution range from fully teleoperated to fully autonomous as well as shared where hand controller inputs from the human operator are mixed with autonomous system inputs in real time. The objective of the shared control environment is to aid the telerobot operator during task execution by merging real-time operator control from hand controllers with autonomous control to simplify task execution for the operator. The operator is the principal command source and can assign as much autonomy for a task as desired. The shared control hardware environment consists of two PUMA 560 robots, two 6-axis force reflecting hand controllers, Universal Motor Controllers for each of the robots and hand controllers, a SUN4 computer, and VME chassis containing 68020 processors and input/output boards. The operator interface for shared control, the User Macro Interface (UMI), is a menu driven interface to design a task and assign the levels of teleoperated and autonomous control. The operator also sets up the system monitor which checks safety limits during task execution. Cartesian-space degrees of freedom for teleoperated and/or autonomous control inputs are selected within UMI as well as the weightings for the teleoperation and autonmous inputs. These are then used during task execution to determine the mix of teleoperation and autonomous inputs. Some of the autonomous control primitives available to the user are Joint-Guarded-Move, Cartesian-Guarded-Move, Move-To-Touch, Pin-Insertion/Removal, Door/Crank-Turn, Bolt-Turn, and Slide. The operator can execute a task using pure teleoperation or mix control execution from the autonomous primitives with teleoperated inputs. Presently the shared control environment supports single arm task execution. Work is presently underway to provide the shared control environment for dual arm control. Teleoperation during shared control is only Cartesian space control and no force-reflection is provided. Force-reflecting teleoperation and joint space operator inputs are planned extensions to the environment.

Backes, Paul G.↗
NASA NTRS1989

Computed torque control of a free-flying cooperat ing-arm robot

The unified approach to solving free-floating space robot manipulator end-point control problems is presented using a control formulation based on an extension of computed torque. Once the desired end-point accelerations have been specified, the kinematic equations are used with momentum conservation equations to solve for the joint accelerations in any of the robot's possible configurations: fixed base or free-flying with open/closed chain grasp. The joint accelerations can then be used to calculate the arm control torques and internal forces using a recursive order N algorithm. Initial experimental verification of these techniques has been performed using a laboratory model of a two-armed space robot. This fully autonomous spacecraft system experiences the drag-free, zero G characteristics of space in two dimensions through the use of an air cushion support system. Results of these initial experiments are included which validate the correctness of the proposed methodology. The further problem of control in the large where not only the manipulator tip positions but the entire system consisting of base and arms must be controlled is also presented. The availability of a physical testbed has brought a keener insight into the subtleties of the problem at hand.

Koningstein, Ross↗
NASA NTRS1992

Neural joint control for Space Shuttle Remote Manipulator System

Neural networks are being used to control a robot arm in a telerobotic operation. The concept uses neural networks for both joint and inverse kinematics in a robotic control application. An upper level neural network is trained to learn inverse kinematic mappings. The output, a trajectory, is then fed to the Decentralized Adaptive Joint Controllers. This neural network implementation has shown that the controlled arm recovers from unexpected payload changes while following the reference trajectory. The neural network-based decentralized joint controller is faster, more robust and efficient than conventional approaches. Implementations of this architecture are discussed that would relax assumptions about dynamics, obstacles, and heavy loads. This system is being developed to use with the Space Shuttle Remote Manipulator System.

Atkins, Mark A.↗
NASA NTRS1983

Computer Control of a Seven Degree of Freedom Manipulator Arm

An algorithm for the computer control of a seven degree of freedom manipulator arm, termed the Hawk Control Mode, is described. The algorithm is segmented into two distinct parts. One part controls the extension, azimuth, and elevation of the wrist joint. The second part controls the attitude of the terminal device. The two segments interact to achieve decoupling of wrist joint translation and terminal device rotation.

Stensby, J.↗
NASA NTRS1993

Integrating Software Modules For Robot Control

Reconfigurable, sensor-based control system uses state variables in systematic integration of reusable control modules. Designed for open-architecture hardware including many general-purpose microprocessors, each having own local memory plus access to global shared memory. Implemented in software as extension of Chimera II real-time operating system. Provides transparent computing mechanism for intertask communication between control modules and generic process-module architecture for multiprocessor realtime computation. Used to control robot arm. Proves useful in variety of other control and robotic applications.

Volpe, Richard A.↗
NASA NTRS2001

Control of a simulated arm using a novel combination of Cerebellar learning mechanisms

We present a model of cerebellar cortex that combines two types of learning: feedforward predicitve association based on local Hebbian-type learning between granule cell ascending branch and parallel fiber inputs, and reinforcement learning with feedback error correction based on climbing fiber activity.

cerebellum cerebellar learning dynamic state estim↗