  Human-robot interaction (HRI) is an important component to improve the
flexibility of modern production lines. However, in real-world applications,
the task (\ie the conditions that the robot needs to operate on, such as the
environmental lighting condition, the human subjects to interact with, and the
hardware platforms) may vary and it remains challenging to optimally and
efficiently configure and adapt the robotic system under these changing tasks.
To address the challenge, this paper proposes a task-agnostic adaptable
controller that can 1) adapt to different lighting conditions, 2) adapt to
individual behaviors and ensure safety when interacting with different humans,
and 3) enable easy transfer across robot platforms with different control
interfaces. The proposed framework is tested on a human-robot handover task
using the FANUC LR Mate 200id/7L robot and the Kinova Gen3 robot. Experiments
show that the proposed task-agnostic controller can achieve consistent
performance across different tasks.
