Chapter 69 — Physical Human-Robot Interaction

An assistive decision-and-control architecture for force-sensitive, hand-arm systems driven via human-machine interfaces (MM2)

This video shows a 2-D pick and place of an object using the Braingate2 neural interface. The robot is controlled through a multipriority Cartesian impedance controller, and its behavior is extended with collision detection and reflex reaction. Furthermore, virtual workspaces are added to ensure safety. On top of this, a decision-and-control architecture, which uses sensory information available from the robotic system to evaluate the current state of task execution, is employed.
Jörn Vogel, Sami Haddadin, John D. Simeral, Daniel Bacher , Beata Jarosiewicz, Leigh R. Hochberg, John P. Donoghue, Patrick van der Smagt