Cloud-based Digital Twin for Cognitive Robotics
arxiv(2024)
摘要
The paper presents a novel cloud-based digital twin learning platform for
teaching and training concepts of cognitive robotics. Instead of forcing
interested learners or students to install a new operating system and bulky,
fragile software onto their personal laptops just to solve tutorials or coding
assignments of a single lecture on robotics, it would be beneficial to avoid
technical setups and directly dive into the content of cognitive robotics. To
achieve this, the authors utilize containerization technologies and Kubernetes
to deploy and operate containerized applications, including robotics simulation
environments and software collections based on the Robot operating System
(ROS). The web-based Integrated Development Environment JupyterLab is
integrated with RvizWeb and XPRA to provide real-time visualization of sensor
data and robot behavior in a user-friendly environment for interacting with
robotics software. The paper also discusses the application of the platform in
teaching Knowledge Representation, Reasoning, Acquisition and Retrieval, and
Task-Executives. The authors conclude that the proposed platform is a valuable
tool for education and research in cognitive robotics, and that it has the
potential to democratize access to these fields. The platform has already been
successfully employed in various academic courses, demonstrating its
effectiveness in fostering knowledge and skill development.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要