Omnidirectional Dual-Arm Aerial Manipulator with Proprioceptive Contact Localization for Landing on Slanted Roofs

TL;DR

This paper introduces a dual-arm aerial manipulator with a proprioceptive contact localization strategy that enables drones to land reliably on slanted roofs by physically sensing surface inclination, independent of external sensing conditions.

Contribution

It presents a novel dual-arm drone design with a momentum-based torque observer for blind surface inclination estimation prior to landing.

Findings

Successfully landed on surfaces with up to 30.5° inclination

Achieved an average inclination estimation error of 2.87°

Validated robustness across multiple experiments

Abstract

Operating drones in urban environments often means they need to land on rooftops, which can have different geometries and surface irregularities. Accurately detecting roof inclination using conventional sensing methods, such as vision-based or acoustic techniques, can be unreliable, as measurement quality is strongly influenced by external factors including weather conditions and surface materials. To overcome these challenges, we propose a novel unmanned aerial manipulator morphology featuring a dual-arm aerial manipulator with an omnidirectional 3D workspace and extended reach. Building on this design, we develop a proprioceptive contact detection and contact localization strategy based on a momentum-based torque observer. This enables the UAM to infer the inclination of slanted surfaces blindly - through physical interaction - prior to touchdown. We validate the approach in flight experiments, demonstrating robust landings on surfaces with inclinations of up to 30.5 degrees and achieving an average surface inclination estimation error of 2.87 degrees over 9 experiments at different incline angles.