A Suitable Hierarchical Framework with Arbitrary Task Dimensions under Unilateral Constraints for physical Human Robot Interaction
This addresses the need for more flexible and intuitive hierarchical frameworks in physical human-robot interaction, though it appears incremental as it builds on existing hierarchical methods.
The paper tackles the problem of managing multiple tasks with arbitrary dimensions while respecting unilateral constraints at position, velocity, acceleration, and force levels in highly-redundant robotic systems, proposing a framework that reacts intuitively to external forces and demonstrates advantages over state-of-the-art approaches in simulations and on a real KUKA LBR iiwa robot.
In the last years, several hierarchical frameworks have been proposed to deal with highly-redundant robotic systems. Some of that systems are expected to perform multiple tasks and physically to interact with the environment. However, none of the proposed frameworks is able to manage multiple tasks with arbitrary task dimensions, while respecting unilateral constraints at position, velocity, acceleration and force level, and at the same time, to react intuitively to external forces. This work proposes a framework that addresses this problem. The framework is tested in simulation and on a real robot. The experiments on the redundant collaborative industrial robot (KUKA LBR iiwa) demonstrate the advantage of the framework compared to state-of-the-art approaches. The framework reacts intuitively to external forces and is able to limit joint positions, velocities, accelerations and forces.