Safety-Critical Reactive Motion Using Constrained Variable Admittance Control with Dual-Type Proximity Sensors
Seung Jae Moon, Hongsik Yim, Hyunchang Kang, Jaeyun Sim, Dawoon Jung, Hyouk Ryeol Choi
AI summary
Problem
Existing reactive collision avoidance methods often fail to distinguish humans from inanimate objects, suffer from inefficient avoidance behaviors, and neglect integrated collision handling, limiting safe simultaneous human-robot cooperation.
Approach
The framework uses dual-type proximity sensors for real-time pre-contact detection and material discrimination to dynamically modulate stiffness and damping via variable admittance control, stabilized by a passivity-preserving energy tank and optimized through quadratic programming.
Key results
- Real-time human and metal object differentiation using dual-type proximity sensors
- Dynamic stiffness and damping modulation for balanced avoidance and contact handling
- Passivity-preserving energy tank mechanism ensuring stability during rapid impedance changes
- Experimental validation demonstrating safe obstacle avoidance and smooth physical interaction
Why it matters
Enables safer, more efficient simultaneous human-robot cooperation by providing a reliable real-time safety fallback for both pre-contact avoidance and post-contact impact in industrial and collaborative settings.
Abstract
We present a method that enhances the safety and responsiveness of robotic manipulators by employing constrained Variable Admittance Control (VAC) in conjunction with prox- imity perception. Recent studies have shown that manipulators equipped with proximity sensors can effectively avoid nearby obstacles in real-time. Nevertheless, unavoidable collisions remain a critical challenge in human-robot interaction (HRI). As a safety fallback, conventional reactive motion algorithms focus on obstacle avoidance but often suffer from inefficiency and disregard collision handling. Our approach integrates proximity- based pre-contact detection and VAC with QP-based motion constraints to proactively adjust impedance parameters while maintaining stable and controlled motion. By dynamically mod- ulating stiffness and damping in response to sensor feedback, the system improves both obstacle avoidance performance and smooth contact handling. Additionally, a passivity-preserving en- ergy tank mechanism mitigates instability arising from parameter variations, ensuring robust and adaptive behavior. Furthermore, experiments involving HRI1 demonstrate that the proposed method ensures both safe avoidance and smooth contact handling. These results suggest that the proposed approach is highly applicable to safety-critical tasks in collaborative and industrial robotic environments.