HITL-D

HITL-D: Human-In-The-Loop Diffusion for Shared Control in Robotic Manipulation

HITL-D is a shared control framework that combines diffusion-based policies with human teleoperation for robotic manipulation tasks. The system autonomously updates end-effector orientation conditioned on scene point clouds and Cartesian position, reducing the number of joystick axes operators must manage. A 12-participant user study found 40% faster task completion, 37% lower perceived workload, and improved subjective ratings versus traditional teleoperation. The work addresses a relatively unexplored intersection of diffusion policy methods and human-in-the-loop control.