Advanced Search
    Wang Zhigang, Wang Haitao, She Qi, Shi Xuesong, Zhang Yimin. Robot 4.0: Continual Learning and Spatial-Temporal Intelligence Through Edge[J]. Journal of Computer Research and Development, 2020, 57(9): 1854-1863. DOI: 10.7544/issn1000-1239.2020.20200254
    Citation: Wang Zhigang, Wang Haitao, She Qi, Shi Xuesong, Zhang Yimin. Robot 4.0: Continual Learning and Spatial-Temporal Intelligence Through Edge[J]. Journal of Computer Research and Development, 2020, 57(9): 1854-1863. DOI: 10.7544/issn1000-1239.2020.20200254

    Robot 4.0: Continual Learning and Spatial-Temporal Intelligence Through Edge

    • With the expansion of the global robot market, robotics is moving from the robot 3.0 era to the robot 4.0 era. In robot 4.0 era, robots should not only have the capability of perception and collaboration, but also have the capability of understanding the environment and making decisions by themselves just like human being. Then they can provide service to people autonomously. Although there have been many breakthroughs in deep learning, it is still a very challenging goal to make robots understand environment and make decisions like humans being. This paper explores three key technologies that are expected to solve these problems: continual learning, spatial-temporal intelligence, and edge computing. Continual learning enables robots to migrate the knowledge of old tasks to the knowledge of new tasks quickly without catastrophic forgotten problems; spatial-temporal intelligence enables robots to establish a bottom-up knowledge representation of the environment and to share and solve problems at different levels. Through edge computing, robots can get more cost-effective computation resource and integrate a variety of intelligence and knowledge easily. It is very useful for the large-scale deployment. These technologies are on the rise, and this paper is just a preliminary analysis.
    • loading

    Catalog

      Turn off MathJax
      Article Contents

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return