Humanoid Robot Detecting Animals via Neural Network

被引:0
|
作者
Yordanov, Yasen E. [1 ]
Mladenov, Valeri M. [1 ]
机构
[1] Tech Univ Sofia, Dept Theory Elect Engn, 8 Kl Ohridski Str, Sofia 1000, Bulgaria
来源
2018 14TH SYMPOSIUM ON NEURAL NETWORKS AND APPLICATIONS (NEUREL) | 2018年
关键词
Aldebaran; NAO robot; Neural network; !text type='Python']Python[!/text; Robot; Tensorflow;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The recognition of objects via neural networks is gaining increasing popularity and usability in the world around us. For example - in the production lines of the factories where the details are recognized and then automatically sorted, in the fully automated stores where the camera systems and deep learning algorithms recognize the products we take from shelves and adds them to a virtual shopping cart, in banks where robots recognize people's faces and offers them different services that the banks provide, or in the autonomous cars where it is needed quick and accurate recognition of the environment around the vehicles. This paper presents a neural network that can identify animals - with an existing set of pictures for training, it can recognize any animal. The pictures are taken from the robot's camera. They're then processed via a convolution neural network which is implemented via Tensorflow on a personal computer. As a result, the robot can identify and say the name of the animal standing in front of it.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] Neural network control of humanoid robot
    Kim D.W.
    Kim N.-H.
    Park G.-T.
    Journal of Institute of Control, Robotics and Systems, 2010, 16 (10) : 963 - 968
  • [2] Efficient Neural Network Approach of Self-Localization for Humanoid Robot
    Chang, Shih-Hung
    Chang, Wei-Hsuan
    Hsia, Chih-Hsien
    Ye, Fun
    Chiang, Jen-Shiun
    JCPC: 2009 JOINT CONFERENCE ON PERVASIVE COMPUTING, 2009, : 149 - 154
  • [3] Developmental word grounding through a growing neural network with a humanoid robot
    He, Xiaoyuan
    Kojima, Ryo
    Hasegawa, Osamu
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2007, 37 (02): : 451 - 462
  • [4] Robot Dynamics Identification via Neural Network
    Dyda, Alexander A.
    Oskin, Dmitry A.
    Artemiev, Andrey V.
    2015 IEEE 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS: TECHNOLOGY AND APPLICATIONS (IDAACS), VOLS 1-2, 2015, : 918 - 923
  • [5] Identification of Robot Forward Dynamics via Neural Network
    Bazzi, Davide
    Messeri, Costanza
    Zanchettin, Andrea Maria
    Rocco, Paolo
    2020 4TH INTERNATIONAL CONFERENCE ON AUTOMATION, CONTROL AND ROBOTS (ICACR 2020), 2020, : 13 - 21
  • [6] Design of a hybrid controller using genetic algorithm and neural network for path planning of a humanoid robot
    Rath, Asita Kumar
    Parhi, Dayal R.
    Das, Harish Chandra
    Kumar, Priyadarshi Biplab
    Mahto, Manjeet Kumar
    INTERNATIONAL JOURNAL OF INTELLIGENT UNMANNED SYSTEMS, 2021, 9 (03) : 169 - 177
  • [7] Online Gait Generation Method Based on Neural Network for Humanoid Robot Fast Walking on Uneven Terrain
    Zhong, Haoran
    Xie, Sicheng
    Li, Xinyu
    Gao, Liang
    Lu, Shengyu
    INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2022, 20 (03) : 941 - 955
  • [8] Online Gait Generation Method Based on Neural Network for Humanoid Robot Fast Walking on Uneven Terrain
    Haoran Zhong
    Sicheng Xie
    Xinyu Li
    Liang Gao
    Shengyu Lu
    International Journal of Control, Automation and Systems, 2022, 20 : 941 - 955
  • [9] Detecting System of Ink Cells in Gravure Cylinder via Neural Network
    He Zifen
    Zhang Yinhui
    2014 SIXTH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA), 2014, : 263 - 266
  • [10] Detecting system of ink cells in gravure cylinder via neural network
    Zhang, Y. (yinhui_z@yahoo.com.cn), 1600, Springer Verlag (215): : 427 - 436