A system on chip-based real-time tracking system for amphibious spherical robots. (6th July 2017)

• Record Type: Journal Article
• Authors: Guo, Shuxiang; Pan, Shaowu; Li, Xiaoqiong; Shi, Liwei; Zhang, Pengyi; Guo, Ping; He, Yanlin
• Is Part Of: International journal of advanced robotic systems. Volume 14:Number 4(2017:Jul./Aug.)
• Publication Date: 2017-07-06
• Subjects: System on chip (SoC) -- detection and tracking system -- heterogeneous computing -- amphibious spherical robot; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881417716559
• Languages: English
• ISSNs: 1729-8806

Abstract

Aiming at vision applications of our amphibious spherical robot, a real-time detection and tracking system adopting Gaussian background model and compressive tracking algorithm was designed and implemented in this article. Considering the narrow load space, the limited power resource and the specialized application scenarios of the robot, a heterogeneous computing architecture combining advanced Reduced Instruction-Set Computer (RISC) machine and field programmable gate array was proposed on the basis of Zynq-7000 system on chip.Under the architecture, main parts of the vision algorithms were implemented as software programs running on the advanced RISC machine-Linux subsystem. And customized image accelerators were deployed on the field programmable gate array subsystem to speed up the time-consuming processes of visual algorithms. Moreover, dynamic reconfiguration was used to switch accelerators online for reducing resource consumption and improving system adaptability. The word length of accelerators was optimized with simulated annealing algorithm to make a compromise between calculation accuracy and resource consumption. Experimental results confirmed the feasibility of the proposed architecture. The single board tracking system was able to provide an image processing rate of up to 89.2 frames per second at the resolution of 320 × 240, which could meet future demands of our robot in biological monitoring and multi-target tracking.