This paper describes a novel home lift, position, and rehabilitation (HLPR) chair, designed at National Institute of Standards and Technology (NIST), to provide independent patient mobility for indoor tasks, such as moving to and placing a person on a toilet or bed, and lift assistance for tasks, such as accessing kitchen or other tall shelves. These functionalities are currently out of reach of most wheelchair users. One of the design motivations of the HLPR Chair is to reduce back injury, typically, an important issue in the care of this group. The HLPR Chair is currently being extended to be an autonomous mobility device to assist cognition by route and trajectory planning. This paper describes the design of HLPR Chair, its control architecture, and algorithms for autonomous planning and control using its unique kinematics.

Cable robots have been extensively used for the loading and unloading of cargo in shipping industries. In this paper, we look at a two-stage cable robot, i.e., a cable robot with two moving platforms connected in series. Sea conditions introduce disturbance into the system. This disturbance is considered while modeling the dynamics of the two-stage cable robot. A robust controller is designed which can assure robust tracking of the desired end-effector trajectory in the presence of the disturbance. The simulation results presented show the effectiveness of the controller.

The U.S. Department of Defense (DoD) requires common architectures that enable the collection, processing, analysis, seamless integration, dissemination, and reuse of information and technology in order to achieve its objectives of interoperability. We attempt to provide a high-level overview of some of the key DoD architectural standards and frameworks and illustrate how the NIST 4D/RCS relates to them.

4D/RCS is the reference model architecture currently being developed for the Demo III Experimental Unmanned Vehicle program. 4D/RCS integrates the NIST (National Institute of Standards and Technology) RCS (real-time control system) with the German (Universitat der Bundeswehr Munchen) VaMoRs 4D approach (3 dimensions+time) to dynamic machine vision. The 4D/RCS architecture consists of a hierarchy of computational nodes each of which contains behavior generation (BG), world modeling (WM), sensory processing (SP), and value judgement (VJ) processes. Each node also contains a knowledge database (KD) and an operator interface. These computational nodes are arranged such that the BG processes represent organizational units within a command and control hierarchy.

Differences between the deliberative and reactive aspects of behaviour have led to different scientific approaches that have divided the field of cognitive research for at least a century. In the tradition of the behaviourist school of psychology, many present day researchers in advanced robotics and artificial intelligence have abandoned inquiry into the complexities of cognitive behaviour in favour of a minimalist philosophy that focuses primarily on stimulus-response reactivity. In contrast, the Real-time Control System (RCS) developed at NIST and elsewhere over the past two decades provides a model for bridging the gap between deliberative and reactive behaviours. RCS is a reference model architecture for intelligent systems design that consists of a hierarchically layered set of processing nodes. In each node, there are both cognitive and reactive elements. At each layer, entities are recognized, tasks are deliberatively planned, and feedback from sensors closes a reactive control loop. RCS thus integrates and distributes deliberative and reactive functions throughout the entire hierarchical architecture, at all levels and time frames. A comparison is made between RCS and subsumption and some illustrative examples of RCS applications are given.

A closed-form solution for obtaining the 3-D structure of a scene for a given six-degree-of-freedom motion of the camera is provided. The solution is massively parallel, i.e., the range that corresponds to each pixel is dependent on the spatial and temporal changes in intensities of that pixel, and on the motion parameters of the camera. The measurements of the intensities are done in a priori known directions. The solution is for the general case of camera motion. The deviation is based upon representing the image in the spherical coordinate system, although a similar approach could be taken for other image domains, e.g., the planar coordinate system. Comments are made on the amount of computations, error and singular points of the solutions. A practical way to significantly reduce and implement them is suggested.>

A theoretical model is proposed consisting of six basic elements: actuators, sensors, sensory processing, world modeling, behavior generation and value judgment. These elements are integrated into a hierarchical system architecture wherein control bandwidth decreases about an order of magnitude from level to level, goals expand in scope and planning horizons expand in space and time about an order-of-magnitude from level to level, and perception of spatial and temporal patterns, models of the world, and memories of events decrease in resolution and expand in spatial and temporal range by about an order-of-magnitude from level to level. At each level, functional modules perform behavior generation, world modeling, sensory processing, and value judgment. Behavior generation modules perform task planning and execution. The world model is the intelligent system's best estimate of the external world. Value judgments provide an evaluation of hypothesized plans, and perceived objects, events, and situations. Sensory processing modules transform sensory maps into world model maps and extract entity attributes and states. Sensory feedback control loops are closed at every level.>

Intelligence is defined as that which produces successful behavior. Intelligence is assumed to result from natural selection. A model is proposed that integrates knowledge from research in both natural and artificial systems. The model consists of a hierarchical system architecture wherein: (1) control bandwidth decreases about an order of magnitude at each higher level, (2) perceptual resolution of spatial and temporal patterns contracts about an order-of-magnitude at each higher level, (3) goals expand in scope and planning horizons expand in space and time about an order-of-magnitude at each higher level, and (4) models of the world and memories of events expand their range in space and time by about an order-of-magnitude at each higher level. At each level, functional modules perform behavior generation (task decomposition planning and execution), world modeling, sensory processing, and value judgment. Sensory feedback control loops are closed at every level.>

Motion relative to a surface is addressed. Image flow can be caused either by motion of objects in the world or by motion of the eye through the world. If knowledge exists of eye motion, dense range maps can be computed locally for all stationary object pixels. Range from image flow can be computed either by gradient methods or by correlation methods. The former are simple but subject to quantization noise. The latter are complex but much more accurate. If eye rotation is known, image flow due to eye translation can be separated from flow due to rotation, and moving objects can be segmented from a stationary background. Topics discussed include the equations of image motion on the egosphere, the method for determining optical flow of B.K.P. Horn and B.G. Schunck (1981), cross correlation, image enhancement by scanning, obstacle avoidance navigation and the temporal integration of image flow.>

The US National Bureau of Standard's multiple autonomous underwater vehicles (MAUV) project involves the development of a real-time intelligent control system that performs sensing, world modeling, planning, and execution for underwater robot vehicles. The goal of the project is to have multiple vehicles exhibiting intelligent, autonomous, cooperative behavior. Initial tests have involved two identical vehicles engaged in various scenarios in Lake Winnipesaukee in New Hampshire. All software for controlling the vehicles reside on computer boards mounted onboard the vehicles.>

Article Free Access Share on Introduction to the Key Word In Context Index (KWIC) to the ACM IS & R symposium Editors: James S. Albus NASA Goddard Space Flight Center NASA Goddard Space Flight CenterView Profile , Jeffrey Yeh University of Maryland University of MarylandView Profile Authors Info & Claims SIGIR '71: Proceedings of the 1971 international ACM SIGIR conference on Information storage and retrievalApril 1971 Pages 225–284https://doi.org/10.1145/511285.511311Published:01 April 1971Publication History 0citation449DownloadsMetricsTotal Citations0Total Downloads449Last 12 Months53Last 6 weeks4 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF