Concept of an Intuitive Human-Robot-Collaboration via Motion Tracking and Augmented Reality
- Resource Type
- Conference
- Authors
- Luipers, Dario; Richert, Anja
- Source
- 2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA) Artificial Intelligence and Computer Applications (ICAICA), 2021 IEEE International Conference on. :423-427 Jun, 2021
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Robotic assembly
Deep learning
Tracking
Service robots
Conferences
Collaboration
Gaussian processes
deep learning
meta learning
motion prediction
Gaussian process
augmented reality
collaborative robotics
- Language
Human-cobot interaction is one of the main aspects of the 4 th industrial revolution. One goal of current robotic research is to enhance safety and efficiency by designing the collaboration in a more intuitive way. The following work introduces two concepts to improve human-cobot collaboration on the basis of deep learning and augmented reality to achieve a more efficient and pleasant working environment. The first concept uses meta learning and Gaussian process to predict the movement of the human worker. The second concept enables the worker to see the next assembly step of the robotic arm via augmented reality.