A fundamental difference between application-specific integrated circuits (ASICs) and field-programmable gate arrays (FPGAs) is that the wires in ASICs are designed to match the requirements of a particular design. Conversely, in an FPGA, the area is fixed and the routing resources exist whether or not they are used. In this paper, we investigate how well several common network topologies map onto a modern FPGA routing fabric. Different multiprocessor network topologies with between 8 and 64 nodes are mapped to a single large FPGA. Except for the fully-connected networks, it is observed that the difference in logic resources used and routing overhead among these topologies is insignificant for the systems tested. Fully-connected networks up to about 22 nodes are also feasible on the same FPGA although the logic and routing utilization clearly grows much faster. The conclusion is that a modern FPGA fabric is very rich in resources and capable of supporting highly interconnected topologies. For systems with a modest number of nodes implemented on current large FPGAs, it is not necessary to use the connectivity-limited topologies typically used for networks-on-chip. Rather, direct point-to-point connections between all communicating nodes can be considered.

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.

Many of the most fundamental examples in probability involve the pose statistics of coins and dice as they are dropped on a flat surface. For these parts, the probability assigned to each stable face is justified based on part symmetry, although most gamblers are familiar with the possibility of loaded dice. In industrial part feeding, parts also arrive in random orientations. We consider the following problem: given part geometry and parameters such as center of mass, estimate the probability of encountering each stable pose of the part. We describe three estimators for solving this problem for polyhedral parts with known center of mass. The first estimator uses a quasistatic motion model that is computed in time O(n log n) for a part with n vertices. The second estimator has the same time complexity but takes into account a measure of dynamic stability based on perturbation. The third estimator uses repeated Monte Carlo experiments with a mechanics simulation package. To evaluate these estimators, we used a robot and computer vision system to record the pose statistics based on 3595 physical drop experiments with four different parts. We compare this data to the results from each estimator. We believe this is the first paper to systematically compare alternative estimators and to correlate their performance with statistically significant experiments on industrial parts.

In automated assembly lines, part feeders often impose a bottleneck that restricts throughput. To facilitate the design of parts and assembly lines, the authors estimate feedrates based on CAD models of parts. A previous paper (Golberg and Craig, 1995) described how to predict throughput for a vision-based robotic part feeder given the distribution of part poses when parts are randomly dropped on a conveyor belt. Estimating this distribution is also useful for the design of traditional feeders such as vibratory bowls. In this paper the authors describe three algorithms for estimating pose distributions. The authors review the quasi-static estimate reported in Wiegley et al. (1992) and introduce a refinement that takes into account some measure of dynamic stability. The perturbed quasi-static estimate can be computed very rapidly and is more accurate than the quasi-static. Still more accurate are estimates based on Monte Carlo simulation using Impulse, although the latter comes at the penalty of increased computation time. The authors compare estimates from all three algorithms with physical experiments.