Search NASA⌕ Search

Engineering topics

Schenker, Paul S.

Publications and source records attributed to Schenker, Paul S..

29 records · Page 2

Interactive and cooperative sensing and control for advanced teleoperation

This paper presents the paradigm of interactive and cooperative sensing and control as a fundamental mechanism of integrating and fusing the strengths of man and machine for advanced teleoperation. The interactive and cooperative sensing and control is considered as an extended and generalized form of traded and shared control. The emphasis of interactive and cooperative sensing and control is given to the distribution of mutually nonexclusive subtasks to man and machine, the interactive invocation of subtasks under the man/machine symbiotic relationship, and the fusion of information and decision-making between man and machine according to their confidence measures. The proposed interactive and cooperative sensing and control system is composed of such major functional blocks as the logical sensor system, the sensor-based local autonomy, the virtual environment formation, and the cooperative decision-making between man and machine. A case study is performed to demonstrate the feasibility of implementing the fundamental theory and system architecture of interactive and cooperative sensing and control, proposed for the new generation of teleoperation.

Lee, Sukhan↗

Software For Integration Of EVA And Telerobotics

Telerobotics/EVA Joint Analysis Systems (TEJAS) computer program is hypermedia information software system using object-oriented programming to bridge gap between crew-EVA and telerobotics activities. TEJAS Version 1.0 contains 20 HyperCard stacks using visual, customizable interface of icon buttons, pop-up menus, and relational commands to store, link, and standardize related information about primitives, technologies, tasks, assumptions, and open issues involved in space-telerobot or crew-EVA tasks. Runs on any Apple MacIntosh personal computer.

Drews, Michael L.↗

Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990

The volume on data fusion from multiple sources discusses fusing multiple views, temporal analysis and 3D motion interpretation, sensor fusion and eye-to-hand coordination, and integration in human shape perception. Attention is given to surface reconstruction, statistical methods in sensor fusion, fusing sensor data with environmental knowledge, computational models for sensor fusion, and evaluation and selection of sensor fusion techniques. Topics addressed include the structure of a scene from two and three projections, optical flow techniques for moving target detection, tactical sensor-based exploration in a robotic environment, and the fusion of human and machine skills for remote robotic operations. Also discussed are K-nearest-neighbor concepts for sensor fusion, surface reconstruction with discontinuities, a sensor-knowledge-command fusion paradigm for man-machine systems, coordinating sensing and local navigation, and terrain map matching using multisensing techniques for applications to autonomous vehicle navigation.

Schenker, Paul S.↗

Fusing human and machine skills for remote robotic operations

The question of how computer assists can improve teleoperator trajectory tracking during both free and force-constrained motions is addressed. Computer graphics techniques which enable the human operator to both visualize and predict detailed 3D trajectories in real-time are reported. Man-machine interactive control procedures for better management of manipulator contact forces and positioning are also described. It is found that collectively, these novel advanced teleoperations techniques both enhance system performance and significantly reduce control problems long associated with teleoperations under time delay. Ongoing robotic simulations of the 1984 space shuttle Solar Maximum EVA Repair Mission are briefly described.

Schenker, Paul S.↗

Sensor-knowledge-command fusion paradigm for man/machine systems

Sensing-knowledge-command (SKC) fusion is presented as a fundamental paradigm of implementing cooperative control for an advanced man-machine system. SKC fusion operates on the 'SKC fusion network,' which represents the connection between sensor data to commands through knowledge. Sensing, knowledge, and command of a human and a machine are tapped into the network to provide inputs, or stimuli, to the network. Such stimuli automatically invoke an SKC fusion process and generate a fused output for cooperative control. Once invoked by stimuli, the SKC fusion process forces the network to converge to a new equilibrium state through the network dynamics composed of data fusion, feature transformation, and constraint propagation. The SKC fusion process thus integrates redundant information, maintains network consistency, identifies faulty data and concepts, and specifies those concepts to be strengthened through sensor planning.

Lee, Sukhan↗

Algorithms and architectures for robot vision

The scope of the current work is to develop practical sensing implementations for robots operating in complex, partially unstructured environments. A focus in this work is to develop object models and estimation techniques which are specific to requirements of robot locomotion, approach and avoidance, and grasp and manipulation. Such problems have to date received limited attention in either computer or human vision - in essence, asking not only how perception is in general modeled, but also what is the functional purpose of its underlying representations. As in the past, researchers are drawing on ideas from both the psychological and machine vision literature. Of particular interest is the development 3-D shape and motion estimates for complex objects when given only partial and uncertain information and when such information is incrementally accrued over time. Current studies consider the use of surface motion, contour, and texture information, with the longer range goal of developing a fused sensing strategy based on these sources and others.

Schenker, Paul S.↗

Sensor fusion II: Human and machine strategies; Proceedings of the Meeting, Philadelphia, PA, Nov. 6-9, 1989

Various papers on human and machine strategies in sensor fusion are presented. The general topics addressed include: active vision, measurement and analysis of visual motion, decision models for sensor fusion, implementation of sensor fusion algorithms, applying sensor fusion to image analysis, perceptual modules and their fusion, perceptual organization and object recognition, planning and the integration of high-level knowledge with perception, using prior knowledge and context in sensor fusion.

Schenker, Paul S.↗

Global models: Robot sensing, control, and sensory-motor skills

Robotics research has begun to address the modeling and implementation of a wide variety of unstructured tasks. Examples include automated navigation, platform servicing, custom fabrication and repair, deployment and recovery, and science exploration. Such tasks are poorly described at onset; the workspace layout is partially unfamiliar, and the task control sequence is only qualitatively characterized. The robot must model the workspace, plan detailed physical actions from qualitative goals, and adapt its instantaneous control regimes to unpredicted events. Developing robust representations and computational approaches for these sensing, planning, and control functions is a major challenge. The underlying domain constraints are very general, and seem to offer little guidance for well-bounded approximation of object shape and motion, manipulation postures and trajectories, and the like. This generalized modeling problem is discussed, with an emphasis on the role of sensing. It is also discussed that unstructured tasks often have, in fact, a high degree of underlying physical symmetry, and such implicit knowledge should be drawn on to model task performance strategies in a methodological fashion. A group-theoretic decomposition of the workspace organization, task goals, and their admissible interactions are proposed. This group-mechanical approach to task representation helps to clarify the functional interplay of perception and control, in essence, describing what perception is specifically for, versus how it is generically modeled. One also gains insight how perception might logically evolve in response to needs of more complex motor skills. It is discussed why, of the many solutions that are often mathematically admissible to a given sensory motor-coordination problem, one may be preferred over others.

Schenker, Paul S.↗

Sensor fusion: Spatial reasoning and scene interpretation; Proceedings of the Meeting, Cambridge, MA, Nov. 7-9, 1988

The present conference discusses topics in the fusion of active and passive sensors, object estimation and verification, three-dimensional representation and knowledge integration, three-dimensional perception from multisensor data, the representation of uncertainty in multisensor fusion, and sensor calibration and registration. Also discussed are the areas of multisensor target detection and classification, multisensor processing architectures, knowledge structures and spatial reasoning, sensory interfaces to telerobotic systems, and navigation with spatial data bases.

Schenker, Paul S.↗

NASA research and development for space telerobotics

The goal of this research is to explore and prove out robust concepts for telerobotic support of space servicing, assembly, maintenance, and telescience tasks. This goal is being addressed through a program of coordinated work in artificial intelligence, robotics, and human factors. The general research objective is the fusion of robot sensing and manipulation, teleoperation, and human and machine cognitive skills into an effective architecture for supervised task automation. NASA is evaluating results of this research program in a ground laboratory telerobot testbed under development at JPL. The testbed development activity includes integrated technology demonstrations. The demonstrations will show telerobot capabilities to perform tasks of increasing complexity, and duration in increasingly unstructured environments. The first such demonstration is the ground-based grappling, dockling, and servicing of a satellite taskboard.

Schenker, Paul S.↗

NASA telerobot testbed development and core technology demonstration

In 1985, NASA initiated a major program of technology development and demonstration for robotics applications to space servicing, assembly, repair, and remote exploration. A ground-based telerobot testbed at the Jet Propulsion Laboratory has been the focal point within this program. Designed to prove technology concepts for supervised automation of increasingly unstructured and complex tasks, the testbed has reached an initial stage of integration. Several significant testbed experiments have been performed, including visual tracking and grapple of a satellite, dual-arm spatial coordination and manipulator control, force-reflecting teleoperations, and simulated task planning for a satellite servicing scenario. The current NASA plans for continuing testbed development and demonstration are also described.

Schenker, Paul S.↗