Azoresbot v2: A new robot for learning robotics and science at schools

被引:3
|
作者
Cascalho, Jose [1 ]
Pedro, Francisco [2 ]
Mendes, Armando [1 ]
Funk, Matthias [1 ]
Ramos, Alberto [3 ]
Novo, Paulo [4 ]
机构
[1] FCT Univ Azores, GRIA LIACC, Ponta Delgada, Acores, Portugal
[2] Escola Basica Integrada Rabo de Peixe, GRIA, Ribeira Grande, Acores, Portugal
[3] Assoc Promocao Desenvolvimento Acores, GRIA, Ponta Delgada, Acores, Portugal
[4] Univ Lisbon, Inst Educ, Lisbon, Portugal
关键词
Robotics Open; Educational Robotics; STEAM; Computer Science;
D O I
10.1109/ICARSC52212.2021.9429815
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper describes the didactic robot Azoresbot v2, a new version of a previous robot Azoresbot already tested in context of robotics open type of events and also at schools. This new version of the robot uses a wifi module providing a way to communicate data received from the sensors as the robot executes its program. It is argued that this feature may be useful to use the robot in competitions extending its use to different learning contents. The robot was built and tested by students in a handson introduction to technology and programming in a Computer Science course for first-year students at the University of the Azores. Since the curriculum was a mix of introductory topics related to digital technology, programming, and data science, the robot must include the following features: be a kit to assemble and test, be easy to program, and provide real-time data that can be analyzed using basic data science techniques. Students completed a questionnaire (N = 13) used to evaluate interaction difficulties with the robot and how students see their importance for learning activity. The survey was based on a previously tested heuristic model. It pointed out some issues to consider in future interactions with the robot in classes and competitions.
引用
收藏
页码:62 / 67
页数:6
相关论文
共 50 条
  • [31] Real-time and Robust Collaborative Robot Motion Control with Microsoft Kinect® v2
    Teke, Burak
    Lanz, Minna
    Kamarainen, Joni-Kristian
    Hietanen, Antti
    2018 14TH IEEE/ASME INTERNATIONAL CONFERENCE ON MECHATRONIC AND EMBEDDED SYSTEMS AND APPLICATIONS (MESA), 2018,
  • [32] Nonclinical pharmacokinetics of a new nonpeptide V2 receptor antagonist, tolvaptan
    Furukawa M.
    Umehara K.
    Kashiyama E.
    Cardiovascular Drugs and Therapy, 2011, 25 (Suppl 1) : S83 - S89
  • [33] PROMISE V2 — something new, something old and something borrowed
    Daniel Koehler
    Nature Reviews Urology, 2023, 20 : 639 - 640
  • [34] 7 DOF Industrial Robot Controlled by Hand Gestures Using Microsoft Kinect v2
    Cueva, Wilson F. C.
    Torres, Hugo M. S.
    Kern, John M.
    2017 IEEE 3RD COLOMBIAN CONFERENCE ON AUTOMATIC CONTROL (CCAC), 2017,
  • [35] A Study on a New EGNOS V2 Release with Enhanced System Performances
    Bauer, F.
    Greze, G.
    Haddad, F.
    Tourtier, A.
    Rols, B.
    Urbanska, K.
    PROCEEDINGS OF THE 32ND INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS+ 2019), 2019, : 902 - 919
  • [36] Is Medieval French diglossic? New evidence on remnant V2 and register
    Larrivee, Pierre
    ISOGLOSS OPEN JOURNAL OF ROMANCE LINGUISTICS, 2022, 8 (02):
  • [37] Supervised learning classifiers for Arabic gestures recognition using Kinect V2
    Hisham, Basma
    Hamouda, Alaa
    SN APPLIED SCIENCES, 2019, 1 (07):
  • [38] Supervised learning classifiers for Arabic gestures recognition using Kinect V2
    Basma Hisham
    Alaa Hamouda
    SN Applied Sciences, 2019, 1
  • [39] CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation
    Zhou, Xingran
    Zhang, Bo
    Zhang, Ting
    Zhang, Pan
    Bao, Jianmin
    Chen, Dong
    Zhang, Zhongfei
    Wen, Fang
    2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR 2021, 2021, : 11460 - 11470
  • [40] Facial skin disease prediction using StarGAN v2 and transfer learning
    Holmes, Kristen
    Sharma, Poonam
    Fernandes, Steven
    INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS, 2023, 17 (01): : 55 - 66