Autonomous eFAST ultrasound scanning by a robotic manipulator using learning from demonstrations

We propose a learning-based controller to enable autonomous execution of the eFAST scanning by a lightweight robotic manipulator according to expert demonstrations. The benefits of this approach are two-fold. Firstly, the automatically acquired USS images can be sent to the expert radiologist from a remote location without the need for complex robotic tele-operation. Secondly, the application of learning by demonstration alleviates the complexity of robotic programming and allows extracting operator-specific knowledge in situ in a natural and intuitive way. The provision of incorporating force information can further improve the versatility of the system, allowing easy adaptation to different dynamic environments.