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Changes in function from fat-depth measurement to meat quality measurement, and vice versa, have occurred in the history of electrical and optical meat probes. In the future, robotic systems might use ultrasonics to measure subcutaneous fat depth while at the same time positioning a fiber-optic probe relative to the skeleton to measure meat quality. There is a major distinction between probes that make a measurement at a single site within the carcass and those that produce a vector of measurements as they move through the carcass. Vector measurements were introduced to find subcutaneous fat thickness, but they may be used for meat quality measurements to deal with intra- and intermuscular variation. Replacement of hand-held probes by robots is in progress and could change meat distribution and marketing, perhaps replacing conventional meat grading by lowering the unit cost of grading and improving reliability for consumers. The feasibility of using ultrasonics to find probe measuring sites in the thoraco-lumbar region of pork carcasses has been proven. This requires new types of carcass morphometry data, such as rib angles and curvatures, and intercostal dimensions.

Abstract-Measurements of received signal strength (RSS) on wireless links provide position information in various localization systems, including multilateration-based and fingerprint-based positioning systems, and device-free localization systems. Existing localization schemes assume a fixed or known transmit power. Therefore, any variation in transmit power can result in error in location estimation. In this paper, we present a generic framework for detecting power attacks and identifying the source of such transmit power variation. Our results show that we can achieve close to zero missed detections and false alarms with RSS measurements of only 50 transmissions. We also present an analysis of trade-off between accuracy and latency of detection for our method.

This paper presents the design, development, and implementation of a kinematic calibration procedure for robot manipulators (that are comprised of closed kinematic chains) working in co-ordination in a multiple robot facility. The objectives of the work described herein were two-fold:(i) to identify the individual kinematic parameters of each robot such as the link lengths, joint angles etc., and(ii) to identify the global kinematic parameters of the multiple robot environment such as the relative positions and Orientations of the individual robot base frames, etc.

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