An Optimization Approach for a Robust and Flexible Control in Collaborative Applications
This addresses safety and reactivity issues in dynamic collaborative environments, but appears incremental as it builds on existing methods like energy tanks and control barrier functions.
The paper tackled the challenge of ensuring both robust stability and high flexibility in human-robot collaboration by proposing a control architecture that combines energy tank-based variable admittance with control barrier functions, and it was experimentally validated on a collaborative robot.
In Human-Robot Collaboration, the robot operates in a highly dynamic environment. Thus, it is pivotal to guarantee the robust stability of the system during the interaction but also a high flexibility of the robot behavior in order to ensure safety and reactivity to the variable conditions of the collaborative scenario. In this paper we propose a control architecture capable of maximizing the flexibility of the robot while guaranteeing a stable behavior when physically interacting with the environment. This is achieved by combining an energy tank based variable admittance architecture with control barrier functions. The proposed architecture is experimentally validated on a collaborative robot.