Focuses on the structure of robot sensing systems and the techniques for measuring and preprocessing 3-D data. To get the information required for controlling a given robot function, the sensing of 3-D objects is divided into four basic steps: transduction of relevant object properties (primarily geometric and photometric) into a signal; preprocessing the signal to improve it; extracting 3-D object features; and interpreting them. Each of these steps usually may be executed by several alternative techniques (tools). Tools for the transduction of 3-D data and data preprocessing are surveyed. The performance of each tool depends on the specific vision task and its environmental conditions, both of which are variable. Such a system includes so-called tool-boxes, one box for each sensing step, and a supervisor, which controls iterative sensing feedback loops and consists of a rule-based program generator and a program execution controller. Sensing step sequences and tools are illustrated for two 3-D vision applications at SRI International Company: visually guided robot arc welding and locating identical parts in a bin.>

A flexible, intelligent robot is regarded as a general purpose machine system that may include effectors, sensors, computers, and auxiliary equipment and, like a human, can perform a variety of tasks under unpredictable conditions. Development of intelligent robots is essential for increasing the growth rate of today's robot population in industry and elsewhere. Robotics research and development topics include manipulation, end effectors, mobility, sensing (noncontact and contact), adaptive control, robot programming languages, and manufacturing process planning. Past achievements and current issues related to each of these topics are described briefly.

This paper describes a sequential procedure for processing registered range and intensity data to detect and extract regions that correspond to planar surfaces in a scene.

Programmable industrial automation can help meet the socioeconomic needs for increased productivity and job enrichment in labor-intensive industries. Characterized by production flexibility and ease of setup for new products, programmable automation is especially adaptable to manufacturing a variety of products in variable lot sizes at mass-production costs. Programmable, automated hardware/software systems existing in industry today include numerical control of machine tools, computer-aided design and manufacturing, production information and control, and industrial robots. These systems are being advanced by ongoing research and development activities; one major activity entails the application of robots with sensors to material-handling, inspection, and assembly operations. The ultimate goal of programmable automation is an essentially unmanned, computer-integrated automatic factory.

An mmf drive NI is applied to the major leg of asaturable ferrite core whose three legs are initially at negative saturation. The resulting Δø in the driven leg divides into the other two (minor) legs, one of which is loaded by a resistive load. This division of flux is analyzed, using for each leg the parabolic inelastic switching model ø = øpeak(F) [1-(ø/øsat)2], which is valid only if mf F is high enough to switch ø to positive saturation. Calculated plots of flux-division ratio D vs NI for various load values are in quite good agreement with experimental data, except in the region of low NI, where the parabolic mdel is invalid for the longer miner leg.