A hardware intelligent processing accelerator for domestic service robots

被引:10
作者
Ishida, Yutaro [1 ]
Morie, Takashi [1 ]
Tamukoh, Hakaru [1 ]
机构
[1] Kyushu Inst Technol, Dept Life Sci & Syst Engn, Kitakyushu, Fukuoka, Japan
基金
日本学术振兴会;
关键词
Robot operating system (ROS); field-programmable gate array (FPGA); domestic service robot; intelligent processing; RoboCup@Home; FPGA COMPONENTS;
D O I
10.1080/01691864.2020.1769726
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
We present a method for implementing hardware intelligent processing accelerator on domestic service robots. These domestic service robots support human life; therefore, they are required to recognize environments using intelligent processing. Moreover, the intelligent processing requires large computational resources. Therefore, standard personal computers (PCs) with robot middleware on the robots do not have enough resources for this intelligent processing. We propose a 'connective object for middleware to an accelerator (COMTA),' which is a system that integrates hardware intelligent processing accelerators and robot middleware. Herein, by constructing dedicated architecture digital circuits, field-programmable gate arrays (FPGAs) accelerate intelligent processing. In addition, the system can configure and access applications on hardware accelerators via a robot middleware space; consequently, robotic engineers do not require the knowledge of FPGAs. We conducted an experiment on the proposed system by utilizing a human-following application with image processing, which is commonly applied in the robots. Experimental results demonstrated that the proposed system can be automatically constructed from a single-configuration file on the robot middleware and can execute the application 5.2 times more efficiently than an ordinary PC.
引用
收藏
页码:947 / 957
页数:11
相关论文
共 26 条
[1]  
Ando N, 2015, P IEEE RSJ INT C INT, P3555
[2]  
[Anonymous], 2016, WORKSH AUT MOB SERV
[3]  
[Anonymous], 2017, P IEEE C COMP VIS PA
[4]  
Bao C, 2017, P C COMP ROB VIS
[5]   High Performance Biological Pairwise Sequence Alignment: FPGA versus GPU versus Cell BE versus GPP [J].
Benkrid, Khaled ;
Akoglu, Ali ;
Ling, Cheng ;
Song, Yang ;
Liu, Ying ;
Tian, Xiang .
INTERNATIONAL JOURNAL OF RECONFIGURABLE COMPUTING, 2012, 2012
[6]   Integrating Stereo Vision with a CNN Tracker for a Person-Following Robot [J].
Chen, Bao Xin ;
Sahdev, Raghavender ;
Tsotsos, John K. .
COMPUTER VISION SYSTEMS, ICVS 2017, 2017, 10528 :300-313
[7]   Data and knowledge mining with big data towards smart production [J].
Cheng, Ying ;
Chen, Ken ;
Sun, Hemeng ;
Zhang, Yongping ;
Tao, Fei .
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION, 2018, 9 :1-13
[8]  
Hori, 2017, PREPRINT
[9]   ROBOCUP@HOME: Analysis and results of evolving competitions for domestic and service robots [J].
Iocchi, Luca ;
Holz, Dirk ;
Ruiz-del-Solar, Javier ;
Sugiura, Komei ;
van der Zant, Tijn .
ARTIFICIAL INTELLIGENCE, 2015, 229 :258-281
[10]  
Ishida Y, 2018, IEEE INT S CIRC SYST