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用于球形两栖机器人的视觉检测与跟踪系统

Visual Detection and Tracking System for a Spherical Amphibious Robot.

作者信息

Guo Shuxiang, Pan Shaowu, Shi Liwei, Guo Ping, He Yanlin, Tang Kun

机构信息

Key Laboratory of Convergence Medical Engineering System and Healthcare Technology, the Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing 100081, China.

Faculty of Engineering, Kagawa University, 2217-20 Hayashicho, Takamatsu, Kagawa 761-0396, Japan.

出版信息

Sensors (Basel). 2017 Apr 15;17(4):870. doi: 10.3390/s17040870.

Abstract

With the goal of supporting close-range observation tasks of a spherical amphibious robot, such as ecological observations and intelligent surveillance, a moving target detection and tracking system was designed and implemented in this study. Given the restrictions presented by the amphibious environment and the small-sized spherical amphibious robot, an industrial camera and vision algorithms using adaptive appearance models were adopted to construct the proposed system. To handle the problem of light scattering and absorption in the underwater environment, the multi-scale retinex with color restoration algorithm was used for image enhancement. Given the environmental disturbances in practical amphibious scenarios, the Gaussian mixture model was used to detect moving targets entering the field of view of the robot. A fast compressive tracker with a Kalman prediction mechanism was used to track the specified target. Considering the limited load space and the unique mechanical structure of the robot, the proposed vision system was fabricated with a low power system-on-chip using an asymmetric and heterogeneous computing architecture. Experimental results confirmed the validity and high efficiency of the proposed system. The design presented in this paper is able to meet future demands of spherical amphibious robots in biological monitoring and multi-robot cooperation.

摘要

为了支持球形两栖机器人的近程观测任务,如生态观测和智能监视,本研究设计并实现了一个移动目标检测与跟踪系统。考虑到两栖环境和小型球形两栖机器人所带来的限制,采用了工业相机和使用自适应外观模型的视觉算法来构建所提出的系统。为了解决水下环境中的光散射和吸收问题,使用了具有颜色恢复算法的多尺度视网膜算法进行图像增强。考虑到实际两栖场景中的环境干扰,使用高斯混合模型来检测进入机器人视野的移动目标。使用具有卡尔曼预测机制的快速压缩跟踪器来跟踪指定目标。考虑到机器人有限的负载空间和独特的机械结构,所提出的视觉系统采用具有非对称和异构计算架构的低功耗片上系统制造。实验结果证实了所提出系统的有效性和高效性。本文提出的设计能够满足球形两栖机器人在生物监测和多机器人协作方面的未来需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fa8/5424747/5bea9ffe07e3/sensors-17-00870-g001.jpg

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