Immersive Demonstrations are the Key to Imitation Learning

TL;DR

This paper demonstrates that immersive force feedback during demonstrations improves the quality and safety of robotic manipulation policies learned through imitation, leading to more consistent and efficient trajectories.

Contribution

It introduces the use of force feedback gloves and robotic rendering to enhance demonstrations, significantly improving imitation learning outcomes in robotic manipulation.

Findings

Force feedback reduces demonstrator fingertip and palm forces.

Force feedback leads to more consistent demonstration trajectories.

Agents trained on these trajectories perform safer and more efficient manipulation.

Abstract

Achieving successful robotic manipulation is an essential step towards robots being widely used in industry and home settings. Recently, many learning-based methods have been proposed to tackle this challenge, with imitation learning showing great promise. However, imperfect demonstrations and a lack of feedback from teleoperation systems may lead to poor or even unsafe results. In this work we explore the effect of demonstrator force feedback on imitation learning, using a feedback glove and a robot arm to render fingertip-level and palm-level forces, respectively. 10 participants recorded 5 demonstrations of a pick-and-place task with 3 grippers, under conditions with no force feedback, fingertip force feedback, and fingertip and palm force feedback. Results show that force feedback significantly reduces demonstrator fingertip and palm forces, leads to a lower variation in demonstrator forces, and recorded trajectories that a quicker to execute. Using behavioral cloning, we find that agents trained to imitate these trajectories mirror these benefits, even though agents have no force data shown to them during training. We conclude that immersive demonstrations, achieved with force feedback, may be the key to unlocking safer, quicker to execute dexterous manipulation policies.