The primary goal of the thesis is to enhance human-robot collaboration by addressing the challenge of real-time dynamic gesture recognition. This initiative is a significant part of the ROMATRIS project, funded by THW at the DFKI, and the focus of the thesis is on the identification and real-time interpretation of specific predefined dynamic gestures. These gestures serve as commands issued by humans to our fully autonomous robots. The main application area for these robots is in disaster relief operations, where they play an important role in assisting rescue operations by autonomously transporting materials, thereby mitigating the risk to the emergency workers. The robot should be able to swiftly and accurately recognize and respond to dynamic gestures, as per the requirement of high-pressure scenarios like disaster relief efforts. And the robot's design shall have integrated robot architecture with dedicated hardware, capable of performing such complex tasks.
In this presentation, the thesis approach will be introduced and the training and evaluation results of the model architectures used for the pipeline be discussed.