Background The Trauma Pod (TP) vision is to develop a rapidly deployable robotic system to perform critical acute stabilization and/or surgical procedures, autonomously or in a teleoperative mode, on wounded soldiers in the battlefield who might otherwise die before treatment in a combat hospital could be provided.
This study explores the reliability of a wireless sensing unit by testing it in a real-world university laboratory environment. The unit employs off-the-shelf products for their key components, while a flexible payload scheme was adopted for radio packet transmission to maximize throughput and minimize latency. The testing consists of two main parts: (1) a series of loopback tests using two off-the-shelf radio components with carrier frequencies of 900 MHz and 2:4 GHz; respectively, and (2) wireless transmission of a shake table response to a periodic swept sine excitation. The performance of the wireless channel is examined in each part of the study. Through this experimental investigation, it is validated that a loopback test may be used as a fast prototyping approach to characterize the complex transmitting environment of a structure in which a wireless monitoring system is installed. Various factors leading to signal attenuation are ranked according to their effects on packet delivery performance. Transmitting range and building materials are among the leading factors causing packet loss (and therefore data loss) in this specific testing environment. The severity of interference from 802.11b wireless systems in close proximity to the wireless sensing unit was investigated. Some preliminary results on the influence of operating rotating machinery and human activities are to wireless sensors were investigated. The results presented herein offer a guideline for applying wireless sensing within real-world structures so that the reliability of the wireless monitoring system is maximized. Due to uncertainties associated with the reliability of wireless communications, statistical analysis is performed on the collected time histories to reveal the underlying patterns associated with data loss. Temporal correlations of data loss were measured and found to be related to the adopted radio. A statistical distribution of the size of consecutive lost data points was further derived from the collected data. Such results have identified the need to further develop: (1) reliable communication
Motion planning in cluttered environments is a weakness of current robotic technology. While research addressing this issue has been conducted, few efforts have attempted to use minimum distance rates of change in motion planning. Geometric influence coefficients provide extraordinary insight into the interactions between a robot and its environment. They isolate the geometry of distance functions from system inputs and make the higher-order properties of minimum distance magnitudes directly available. Knowledge of the higher order properties of minimum distance magnitudes can be used to predict the future obstacle avoidance, path planning, and/or target acquisition state of a manipulator system and aid in making intelligent motion planning decisions. Here, first and second order geometric influence coefficients for minimum distance magnitudes are rigorously developed for several simple modeling primitives. A general method for similar derivations using new primitives and an evaluation of finite difference approximations versus analytical second order coefficient calculations are presented. Two application examples demonstrate the utility of minimum distance magnitude influence coefficients in motion planning.
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