Robot Perception through Wearable Sensors: Decoding Grasping for Human-Robot Hand-Over

Human-robot interaction represents the cornerstone
for the full development of Industry 4.0 and 5.0 paradigms, that
rely on this cooperation in order to develop more efficient and
flexible production lines. In this context, the human-robot handover
plays a crucial role and many approaches were introduced
to plan and control this task, including the less investigated
decoding of human muscles activity. Hence, the design of reliable
myoelectric human-robot interfaces is a point of primary interest.
This paper investigates the use of a wearable device, i.e. an
armband, for achieving a robust detection of several human
grasping gestures. An evaluation of the most useful features,
belonging to three different computational domains, is also
proposed. Outcomes showed that high recognition performance
can be achieved with limited computational burden, which is
crucial when dealing with real-time demands in collaborative
task.