You're Pushing My Buttons: Instrumented Learning of Gentle Button Presses

Raman Talwar

Keywords: Instrumentation, Diffusion Policy, Multimodal Learning, Audio-Tactile Integration, Robotic Manipulation

TL;DR: We show that training-time instrumentation improves performace in manipulation policies without creating inference-time dependence

Abstract:

Learning contact-rich manipulation is difficult from cameras and proprioception alone because contact events are only partially observed. We test whether training-time instrumentation, i.e., object sensorisation, can improve policy performance without creating deployment-time dependencies.
Specifically, we study button pressing as a testbed and use a microphone fingertip to capture contact-relevant audio. We use an instrumented button-state signal as privileged supervision to fine-tune an audio encoder into a contact event detector. We combine the resulting representation with imitation learning using three strategies, such that the policy only uses vision and audio during inference.
Button press success rates are similar across methods, but instrumentation-guided audio representations consistently reduce contact force. These results support instrumentation as a practical training-time auxiliary objective for learning contact-rich manipulation policies.

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Submission Number: 13