This paper demonstrates fundamental problems with dexterity measures found throughout the robotics literature and offers a methodology for correcting those problems. Measures of robot dexterity derived from eigenvalues, eigenvectors, similarity transformations, singular-value decompositions and the Moore-Penrose inverse of the manipulator Jacobian do not have invariant physical meaning. The paper presents manipulability ellipsoids and manipulability screw-subspaces for both redundant and nonredundant manipulators.>

A presentation is made of a structure-function (S-F) paradigm for representing engineering designs. The S-F paradigm treats structures and functions as first-class objects by modeling the physical configuration of the design as structural objects and the behavior of the design as functional objects. The paradigm supports engineering designs by using the associative knowledge between structures and functions to help in the design process and to support simulation by providing for a run-time interaction between structures and functions. The S-F paradigm would be generally applicable to model the passive and active information in any complex system. It may be implemented as a layer on top of any object-oriented model.>

An extended description of a representation for discrete assembly sequences, the discrete task planning tree (DTP tree), is presented. A study of the maximum number of valid discrete assembly sequences generated, K, is made, and the effects of assembly rules and assembly constraints on K are studied. The DTP tree is generated offline, but it is stored for online use in assembly error recovery or for opportunistic assembly. A prototype of the task sequence generator using the DTP tree was implemented in Lisp on a PC.>

An application of the object-oriented semantic association model (OSAM) concepts to the modeling of parts and their relationships, including assembly operations, is presented. It is shown that the semantic primitives (facilities) of OSAM make it possible to model the necessary structural relationships and constraints adequately. The proposed scheme can be used for simulation and task planning in the workcell environment.>

A memory organized around a major/minor loop magnetic bubble storage unit contains database information in relational form. An external marker memory, consisting of an M-bit shift register or an M X 1 RAM, provides, in conjunction with an assumed processing element, an associative search capability. Each bit accumulates search results of a query applied to its corresponding bubble page. The number of pages M equals the minor loop length and N, the page size, equals the number of minor loops in the bubble memory. A systematic series of performance-improving access strategies and architectural modifications are applied to an existing major/minor loop bubble device to determine the effects of each change. In all cases data access-time formulas reveal that positioning a marked page for access is a linear function of the minor loop length M, while outputting the marked pages via the bubbles serial output bus is a quadratic function of M. An evaluation and relative comparison of these architectures indicate that a segmented, nondestructive major/minor loop transfer function can enhance current magnetic bubble memory (MBM) performance in relational data processing by an order of magnitude.

This paper proposes a novel design for a parallel nonadaptive binary pattern classifier. The structure employs random-pulse (stochastic) computing elements to economically realize multimodal nonlinear discriminant functions similar in form to those used in potential function classifiers. The technique achieves efficient hardware utilization by employing a READ-ONLY memory (ROM) without addressing circuits to store modes and simultaneously execute parallel stochastic multiplications required in discriminant function computations.

The concept of lossless state or system is generalized by the definition of k-losslessness. If k>N( N-1)/2 for an N-state machine, k-lossless implies lossless. The series connection of a set of discrete time systems {Ai}, where Ai is ki-lossless, results in a system which is min{ki}-lossless. This result is a simple verification of the intuitive notion that a noiseless communication channel is only as lossless as the most lossy system in the channel. By means of input- output pair analysis, systems with the decomposition property (one of the necessary but not sufficient conditions for linearity) are shown to be information-lossless of finite order m, when one state has finite order m. Further, every state must have exactly the same order. For an N-state system with decomposition and zero-state linearity, information-lossless implies information-lossless of finite order m≤N. As a consequence, all information-lossless linear sequential machines used as encoders allow decoding to begin after m received symbols, provided that the encoder's starting state is known in advance.

The decomposition property, a necessary condition for linearity, is defined for discrete-time systems. N-state machines with this property have finite memory μ≤N−1. Linear and autonomous systems are important classes of systems with decomposition. Several representations of systems with decomposition are given and a general form of the discrete-time state equations for a finite-memory system with decomposition is derived. An algorithm is developed by which an arbitrary complete-sequential machine may be tested for decomposition.