Assistive force control in collaborative human-robot transportation

Collaborative robotics has gained significant traction in the industrial scenario due to its ability to merge human cognitive abilities with robot strength and dexterity. One specific area where this technology is promising is the transportation of heavy and/or bulky objects. In the scenarios where the human leads, physical human-robot interaction triggers cognitive human-robot interaction, by which the robot is called to adapt its behavior to the collaborator's intention. Based on this principle, this paper introduces a novel control architecture, namely assistive force control (AFC), by which the robot's purpose is to alleviate the human collaborator's effort during transportation. Instead of acting on the robot's motion, the AFC acts on its causes, by intuitively defining assistive forces, which are input to a lower-level direct force controller. We validate the proposed architecture on two real-case transportation scenarios involving an industrial robot collaboratively carrying objects with different subjects. Our preliminary results show that low effort is required for human operators to manipulate heavy objects, confirming that the proposed architecture is well-suited for collaborative transportation in real-world scenarios.