Real-time moving object recognition and tracking using computation offloading

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems Pub Date : 2010-12-03 DOI:10.1109/IROS.2010.5650303

Yamini Nimmagadda, Karthik Kumar, Yung-Hsiang Lu, C. S. G. Lee

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引用次数: 87

Abstract

Mobile robots are widely used for computation-intensive tasks such as surveillance, moving object recognition and tracking. Existing studies perform the computation entirely on robot processors or on dedicated servers. The robot processors are limited by their computation capability; real-time performance may not be achieved. Even though servers can perform tasks faster, the communication time between robots and servers is affected by variations in wireless bandwidths. In this paper, we present a system for realtime moving object recognition and tracking using computation offloading. Offloading migrates computation to servers to reduce the computation time on the robots. However, the migration consumes additional time, referred as communication time in this paper. The communication time is dependent on data size exchanged and the available wireless bandwidth. We estimate the computation and communication needed for the tasks and choose to execute them on robot processors or servers to minimize the total execution time, in order to satisfy real-time constraints.

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基于计算卸载的实时运动目标识别与跟踪

移动机器人被广泛用于计算密集型任务，如监视、移动物体识别和跟踪。现有的研究完全在机器人处理器或专用服务器上进行计算。机器人处理器的计算能力有限;可能无法实现实时性能。尽管服务器可以更快地执行任务，但机器人和服务器之间的通信时间受到无线带宽变化的影响。本文提出了一种基于计算卸载的实时运动目标识别与跟踪系统。卸载将计算迁移到服务器，以减少机器人的计算时间。但是，迁移会消耗额外的时间，本文将其称为通信时间。通信时间取决于交换的数据大小和可用的无线带宽。我们估计了任务所需的计算和通信，并选择在机器人处理器或服务器上执行它们，以最小化总执行时间，以满足实时约束。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

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