We describe a system that allows a distributed group of users to simultaneously teleoperate an industrial robot arm via the Internet. A Java applet at each client streams mouse motion vectors from up to 3D users; a sewer aggregates these inputs to produce a single control stream for the robot. Users receive visual feedback from a digital camera mounted above the robot arm. To our knowledge, this is the first collaboratively controlled robot on the Internet.

We consider a sensorless approach to feeding parts on a conveyor belt using pins (rigid barriers) to topple parts into desired orientations. Given the 2D projection of an n-sided convex polyhedral part, its center of mass, and coefficients of friction, we give an O(n/sup 2/) algorithm to compute the "toppling graph", a new data structure that represents the mechanics of toppling, including rolling and jamming. The toppling graph can be used to identify critical pin heights that permit toppling. We compare pin heights predicted by the graph with physical experiments, and give a complete O(n/sup 3n/) algorithm for designing pin sequences.

The vibratory bowl feeder is the oldest and still most common approach to the automated feeding (orienting) of industrial parts. We consider a class of vibratory bowl filters that can be described by removing polygonal sections from the track; we refer to this class of filters as traps. For an n-sided convex polygonal part and m-sided convex polygonal trap, we give an O((n+m)log(n+m)) algorithm to decide if the part will be rejected by the trap, and an O((nm(n+m))/sup 1+/spl epsiv//) algorithm which deals with non-convex parts and traps. We then consider the problem of designing traps for a given part, and consider two rectilinear subclasses, balconies and gaps. We give linear and O(n/sup 2/) algorithms for designing feeders and have tested the results with physical experiments using a commercial inline vibratory feeder.

We propose a new model for gripping parts with an industrial parallel-jaw gripper. In contrast to many previous models, we use two grip points and define candidate grips that are resistant to slipping and torque about the part's center of mass. These grips must also be accessible and robust to perturbations in part position. We give an O(n/sup 3/) algorithm for computing and ranking O(n/sup 2/) such grips on an n-sided polygonal slice through the part. The algorithm will be part of a design and simulation system that can rapidly provide feedback to designers; thus it must run quickly and reliably. We have also implemented the algorithm in a Java applet with a graphical user interface that allows Internet users to define a part; the applet computes, ranks, and displays the set of computed grips.

This paper describes the application of neural network techniques to the papermaking industry, particularly for the prediction of paper "curl." Paper curl is an important quality measure that can only be measured reliably off-line after manufacture, making it difficult to control. Here we predict, before paper manufacture from characteristics of the current reel, whether the paper curl will be acceptable and the level of curl. For both the case of predicting the probability that paper will be "out-of-specification" and that of predicting the level of curl, we include confidence intervals indicating to the machine operator whether the predictions should be trusted. The results and the associated discussion describe a successful application of neural networks to a difficult, but important, real-world task taken from the papermaking industry. In addition the techniques described are widely applicable to industry where direct prediction of a quality measure and its acceptability are desirable, with a clear indication of prediction confidence.

No abstract available.

The advantages of TCB (trusted computing base) subsetting for building multilevel database systems are discussed, and the architectural impact on the database system when the TCB subsetting approach is used in a real implementation is described. Particular attention is given to such areas of difficulty as concurrency controls, recovery management, and buffer management. In discussing implications for the architecture of the database system, it is noted that the standard ORACLE database system already supports those architectural features that are required, and ORACLE is proceeding with product development and product evaluation projects to extend the promise of TCB subsetting to commercially available ORACLE RDBMS (relational database management system) products on a wide variety of platforms. The SeaView prototype takes advantage of the architectural features of ORACLE with a TCB subsetting approach to achieve a class A1 system that reuses existing TCB and database technology.>