Research on human-robot interaction for robotic spatial 3D printing based on real-time hand gesture control

被引:0
|
作者
Shi, Xinyu [1 ,2 ]
Wang, Chaoran [1 ]
Shi, Liyu [1 ]
Zhou, Haining [2 ]
Phillips, Tyson Keen [3 ]
Bi, Kang [2 ]
Cui, Weijiu [1 ]
Sun, Chengpeng [2 ]
Wan, Da [4 ]
机构
[1] Qingdao Univ Technol, Coll Architecture & Urban Planning, iSMART, Qingdao 266033, Peoples R China
[2] Univ Kitakyushu, Fac Environm Engn, Fukuoka 8080135, Japan
[3] Piaggio Fast Forward Co Ltd, Boston, MA 02129 USA
[4] Tianjin Chengjian Univ, Sch Architecture, Tianjin 300384, Peoples R China
基金
中国国家自然科学基金;
关键词
Robotic spatial 3D printing; Human-robot interaction; Real-time control; Gesture recognition; Deep learning; FRAMEWORK;
D O I
10.1016/j.rcim.2024.102788
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
With the rapid advancements in three-dimensional (3D) printing, researchers have shifted their focus towards the mechanical systems and methods used in this field. While Fused Deposition Modelling (FDM) remains the dominant method, alternative printing methods such as Spatial 3DP (S-3DP) have emerged. However, the majority of existing research on 3D printing technology has been emphasizing offline control, which lacks the capability to dynamically adjust the printing path in real time. Such an limitation has resulted in a decrease in printing efficiency. Therefore, this paper proposes a human-robot interaction (HRI) method based on real-time gesture control for Robotic Spatial 3DP (RS-3DP). This method incorporates utilization of YOLOv5 and Mediapipe algorithms to recognize gestures and convert the gesture information into real-time robot operations. Results show that this approach offers a feasible solution to address the issue of discontinuous S-3DP nodes because it achieves a gesture-controlled robot movement accuracy of 91 % and an average system response time of approximately 0.54 s. The proposed HRI method represents a pioneering advancement in real-time control for RS-3DP, thereby paving the way for further exploration and development in this field.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] A Human-Robot Interaction for a Mecanum Wheeled Mobile Robot with Real-Time 3D Two-Hand Gesture Recognition
    Luo, Xueling
    Amighetti, Andrea
    Zhang, Dan
    [J]. 2019 3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, AUTOMATION AND CONTROL TECHNOLOGIES (AIACT 2019), 2019, 1267
  • [2] 3D Hand and Object Pose Estimation for Real-time Human-robot Interaction
    Bandi, Chaitanya
    Kisner, Hannes
    Thomas, Urike
    [J]. PROCEEDINGS OF THE 17TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISAPP), VOL 4, 2022, : 770 - 780
  • [3] Real-time vision based gesture recognition for human-robot interaction
    Hong, Seok-ju
    Setiawan, Nurul Arif
    Lee, Chil-woo
    [J]. KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS: KES 2007 - WIRN 2007, PT I, PROCEEDINGS, 2007, 4692 : 493 - +
  • [4] An Integrated Real-Time Hand Gesture Recognition Framework for Human-Robot Interaction in Agriculture
    Moysiadis, Vasileios
    Katikaridis, Dimitrios
    Benos, Lefteris
    Busato, Patrizia
    Anagnostis, Athanasios
    Kateris, Dimitrios
    Pearson, Simon
    Bochtis, Dionysis
    [J]. APPLIED SCIENCES-BASEL, 2022, 12 (16):
  • [5] Dynamic Hand Gesture Recognition Based on 3D Hand Pose Estimation for Human-Robot Interaction
    Gao, Qing
    Chen, Yongquan
    Ju, Zhaojie
    Liang, Yi
    [J]. IEEE SENSORS JOURNAL, 2022, 22 (18) : 17421 - 17430
  • [6] Real-time 3D Hand Gesture Based Mobile Interaction Interface
    Che, Yunlong
    Song, Yuxiang
    Qi, Yue
    [J]. ADJUNCT PROCEEDINGS OF THE 2019 IEEE INTERNATIONAL SYMPOSIUM ON MIXED AND AUGMENTED REALITY (ISMAR-ADJUNCT 2019), 2019, : 228 - 232
  • [7] Real-Time Face and Gesture Analysis for Human-Robot Interaction
    Wallhoff, Frank
    Rehrl, Tobias
    Mayer, Christoph
    Radig, Bernd
    [J]. REAL-TIME IMAGE AND VIDEO PROCESSING 2010, 2010, 7724
  • [8] Real-Time Hand Gesture Recognition for Human Robot Interaction
    Correa, Mauricio
    Ruiz-del-Solar, Javier
    Verschae, Rodrigo
    Lee-Ferny, Jong
    Castillo, Nelson
    [J]. ROBOCUP 2009: ROBOT SOCCER WORLD CUP XIII, 2010, 5949 : 46 - 57
  • [9] A real-time human-robot interaction framework with robust background invariant hand gesture detection
    Mazhar, Osama
    Navarro, Benjamin
    Ramdani, Sofiane
    Passama, Robin
    Cherubini, Andrea
    [J]. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2019, 60 : 34 - 48
  • [10] Real-time Gender Recognition Based on 3D Human Body Shape for Human-Robot Interaction
    Luo, Ren C.
    Wu, Xiehao
    [J]. HRI'14: PROCEEDINGS OF THE 2014 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION, 2014, : 236 - 237