Minimalist Compliance Control

TL;DR

This paper introduces Minimalist Compliance Control, a method enabling safe, compliant robot interaction using only standard actuator signals, eliminating the need for force sensors or complex learning, and validated across various robots and tasks.

Contribution

It presents a novel compliance control approach that relies solely on readily available actuator signals, avoiding force sensors and learning, and is adaptable to multiple robot platforms.

Findings

Robust and safe compliance achieved without force sensors.

Applicable across diverse robot types and control paradigms.

Validated on multiple robots with successful contact-rich task execution.

Abstract

Compliance control is essential for safe physical interaction, yet its adoption is limited by hardware requirements such as force torque sensors. While recent reinforcement learning approaches aim to bypass these constraints, they often suffer from sim-to-real gaps, lack safety guarantees, and add system complexity. We propose Minimalist Compliance Control, which enables compliant behavior using only motor current or voltage signals readily available in modern servos and quasi-direct-drive motors, without force sensors, current control, or learning. External wrenches are estimated from actuator signals and Jacobians and incorporated into a task-space admittance controller, preserving sufficient force measurement accuracy for stable and responsive compliance control. Our method is embodiment-agnostic and plug-and-play with diverse high-level planners. We validate our approach on a robot arm, a dexterous hand, and two humanoid robots across multiple contact-rich tasks, using vision-language models, imitation learning, and model-based planning. The results demonstrate robust, safe, and compliant interaction across embodiments and planning paradigms.