Landing gear design for emergency take-off and landing of drones on unconventional landings

Zhao Wang

doi:10.1117/12.3027186

1 April 2024 Landing gear design for emergency take-off and landing of drones on unconventional landings

Zhao Wang

Proceedings Volume 13077, Fourth International Conference on Signal Processing and Machine Learning (CONF-SPML 2024); 130770R (2024) https://doi.org/10.1117/12.3027186
Event: 4th International Conference on Signal Processing and Machine Learning (CONF-SPML 2024), 2024, Chicago, IL, United States

Abstract

The drone landing gear is an important load-bearing component on the drone. Especially for small UAVs with short endurance time, poor landing performance and high failure rate, the landing gear is a key component to protect the airframe from damage when landing in various complex environments. Therefore, it is of great value to find the right landing gear for a variety of environments. However, some of the drone landing gear that already exists on the market today mostly has very limited protection for drones. Therefore, in view of the problems existing in civilian small UAVs and the functional blind spots not involved in the existing UAV landing gear on the market, an inflatable UAV landing gear was conceived. In this paper, ANSYS software was used to model and simulate the stress analysis of the three types of landing gear landing on uneven hard planes (simulating hard roads and potholes) and flat plates prone to collapse (simulating snow and sand) on straight rod landing gear, skid landing gear, and inflatable airbag landing gear. Find out the limitations of straight and skid landing gear, as well as the advantages of inflatable airbag landing gear. And put forward the design concept of the inflatable UAV landing gear.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhao Wang "Landing gear design for emergency take-off and landing of drones on unconventional landings", Proc. SPIE 13077, Fourth International Conference on Signal Processing and Machine Learning (CONF-SPML 2024), 130770R (1 April 2024); https://doi.org/10.1117/12.3027186

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KEYWORDS

Unmanned aerial vehicles

Design

Roads

Safety

Computer simulations

Sand

Astatine

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