Interactive Human–Robot Skill Transfer: A Review of Learning Methods and User Experience

Abstract

Figure 3. A broad view of LfD approaches considering user experience. Red arrows indicate the direct interaction that can be perceived by the user while blue arrows indicate the background operation that cannot be perceived by the user.

Peripheral Neuroergonomics – An Elegant Way to Improve Human-Robot Interaction?

“…These HMIs must rather resort to interpreting the user's intent based on signals the user is able to produce -usually, relevant biological signals related to the intended muscle activation (Beckerle et al, 2019). Surface electromyography (Merletti et al, 2011) is a primary example, although different kinds of signals are currently being explored, e.g., tactile information (Beckerle et al, 2018(Beckerle et al, , 2019 and also promising for other applications such as anthropomorphic teleoperation (Nostadt et al, 2020) or teaching collaborative robots (Cansev et al, 2021).…”