2015 CPS PI MTG Videos, Posters, and Abstracts
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Despite many advances in vehicle automation, much remains to be done: the best autonomous vehicle today still lags behind human drivers, and connected vehicle (V2V) and infrastructure (V2I) standards are only just emerging. In order for such cyber-physical systems to fully realize their potential, they must be capable of exploiting one of the richest and most complex abilities of humans, which we take for granted: seeing and understanding the visual world.
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Team decision problems are a static simplification of decentralized Markov decision problems, and form a fundamental building block of decentralized control problems. An early paper by Radner showed that, in the special case when all random variables are Gaussian and the cost function is quadratic, there exist optimal policies that are linear functions. However, Tsitsiklis and Athans proved that the general case is NP-hard.
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Many safety-critical cyber-physical systems rely on advanced sensing capabilities to react to changing environmental conditions. However, cost-effective deployments of such capabilities have remained elusive. Such deployments will require software infrastructure that enables multiple sensor-processing streams to be multiplexed onto a common hardware platform at reasonable cost, as well as tools and methods for validating that required processing rates can be maintained.
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This poster presents progress of the synergistic framework and algorithms development for a group sensors to collaborate in disaster scenarios. A number of fundamental research results were obtained on scene understanding in a network of visual sensors. These were experimentally evaluated, and datasets and results from these evaluations have been released to the community.
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Stochastic hybrid systems are a class of stochastic models that incorporates both continuous- and discretestate dynamics. They have wide applications in modeling various processes, such as communication networks [4] and biochemical reactions [6]. In this work, we focus on continuous-time stochastic hybrid systems (CTSHS); specifically, we propose a framework using Metric Interval Temporal Logic (MITL) [1] to describe the systems' behavior and verifying the MITL formulas via model reduction and sampling.
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Recent progress in battery technology has made it possible to use batteries to power various physical platforms, such as ground/air/water vehicles. These platforms require hundreds/thousands of battery cells to meet their power and energy needs. Of these, automobiles, locomotives, and unmanned air vehicles (UAVs) face the most stringent environmental challenges.
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This project, NSF grant 1329363, is a modular, computationally-distributed multi-robot cyber-physical system (CPS) for assisting young developmentally-delayed children learning to walk. The challenges of assisting young developmentally-delayed children learning to walk are 1) stabilizing medio-lateral body sway, 2) developing gait that exploits energy exchange, and 3) coordinating multiple degrees of freedom.
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Commodity operating systems manage time in a best effort fashion, where clock synchronization is performed independently of both application demand and resource constraints. The vision of the RoseLine project is to develop a Quality of Time (QoT) stack for Linux that enables developers to write distributed applications that perform computation with a common sense of time.
