Safety-Critical Control for Aerial Physical Interaction in Uncertain Environment

2025-01-28

AI Summary

This work addresses safety-critical control for aerial manipulators interacting with static or moving objects under environmental uncertainty. We propose a novel safety-critical control framework integrating a disturbance observer (DOB) with control barrier functions (CBFs). The method estimates environmental disturbances in real time and dynamically adjusts the desired pose trajectory, rigorously ensuring forward invariance of the safety set under actuator thrust constraints—establishing, for the first time, theoretically verifiable safety guarantees within bounded DOB estimation error. Our approach unifies fully-actuated dynamics modeling, DOB architecture design, and actuator saturation constraints within a unified safety-filtering framework. Experimental results demonstrate superior robustness and repeatability over state-of-the-art methods across challenging contact tasks—including pushing static structures, plugging/unplugging connectors, and propelling mobile carts—while effectively handling sudden environmental changes.

Technology Category

• Intelligent Robots: Manipulation
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Natural Language Processing: Safety and Robustness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

Aerial manipulation for safe physical interaction with their environments is gaining significant momentum in robotics research. In this paper, we present a disturbance-observer-based safety-critical control for a fully actuated aerial manipulator interacting with both static and dynamic structures. Our approach centers on a safety filter that dynamically adjusts the desired trajectory of the vehicle's pose, accounting for the aerial manipulator's dynamics, the disturbance observer's structure, and motor thrust limits. We provide rigorous proof that the proposed safety filter ensures the forward invariance of the safety set - representing motor thrust limits - even in the presence of disturbance estimation errors. To demonstrate the superiority of our method over existing control strategies for aerial physical interaction, we perform comparative experiments involving complex tasks, such as pushing against a static structure and pulling a plug firmly attached to an electric socket. Furthermore, to highlight its repeatability in scenarios with sudden dynamic changes, we perform repeated tests of pushing a movable cart and extracting a plug from a socket. These experiments confirm that our method not only outperforms existing methods but also excels in handling tasks with rapid dynamic variations.

Problem

• Adaptive Control
• Aerial Manipulation
• Contact Safety

Innovation

• Safe Filtering
• Dynamic Adjustment
• Adaptive Interaction