Moth: A Low-Cost IR-Based Approach towards Autonomous Precision Drone Landing
Yanchen Liu, Minghui Zhao, Kaiyuan Hou, Junxi Xia, Charles Carver, Stephen Xia, Xia Zhou, Xiaofan Jiang
Abstract
As micro-drones become increasingly deployed in indoor environments for applications ranging from warehouse inspection to emergency response, the challenge of precise automated landing emerges as a crucial barrier to their practical operation and ubiquitous adoption. Existing landing approaches often require complex hardware and substantial computation or perform unreliably indoors, making them impractical for palm-sized microdrones. We propose Moth, a low-cost infrared light-based solution that targets precise and efficient landing of low-resource microdrones. Moth consists of an infrared light source at the landing station along with an energy-efficient photodiode (PD) sensing platform attached to the bottom of the drone. At a cost under 83 USD, Moth achieves comparable performance to vision-based methods but at a fraction of the energy consumption and computation. Moth requires only three PDs without any complex pattern recognition models to land the drone accurately, under 10 cm of error, from up to 11.1 meters away.