A Gravity Balanced Test Stand for Flight Testing of Small/Micro Unmanned Aerial Vehicles

Author(s):  
Qi Lu ◽  
Carlos E. Ortega ◽  
Ou Ma

For the purpose of safety, test stands are usually needed for testing unmanned aerial vehicles (UAVs), especially in the early test stage. Although a test stand can prevent the tested vehicle from flying away or crashing, it adds extra burden to the vehicle due to the weight of its moving mechanism. This can be a major problem for micro aerial vehicles (MAVs) because of their tiny lifting or payload capability. This paper presents an innovative solution to this problem by designing a passive gravity balanced test stand. The stand is capable of completely compensating its own weight, so that the tested vehicle will not have the extra burden from the weight of the test stand. To verify the feasibility of the design, a simulation study has been conducted, which demonstrated the benefits of the new design.

2009 ◽  
Vol 1 (3) ◽  
pp. 155-171 ◽  
Author(s):  
Jon N. Ostler ◽  
W. Jerry Bowman ◽  
Deryl O. Snyder ◽  
Timothy W. McLain

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4186
Author(s):  
Muhammad Hassan Tanveer ◽  
Antony Thomas ◽  
Waqar Ahmed ◽  
Hongxiao Zhu

Unmanned aerial vehicles (UAVs) have shown great potential in various applications such as surveillance, search and rescue. To perform safe and efficient navigation, it is vitally important for a UAV to evaluate the environment accurately and promptly. In this work, we present a simulation study for the estimation of foliage distribution as a UAV equipped with biosonar navigates through a forest. Based on a simulated forest environment, foliage echoes are generated by using a bat-inspired bisonar simulator. These biosonar echoes are then used to estimate the spatial distribution of both sparsely and densely distributed tree leaves. While a simple batch processing method is able to estimate sparsely distributed leaf locations well, a wavelet scattering technique coupled with a support vector machine (SVM) classifier is shown to be effective to estimate densely distributed leaves. Our approach is validated by using multiple setups of leaf distributions in the simulated forest environment. Ninety-seven percent accuracy is obtained while estimating thickly distributed foliage.


2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Caleb Rice ◽  
Yu Gu ◽  
Haiyang Chao ◽  
Trenton Larrabee ◽  
Srikanth Gururajan ◽  
...  

Autonomous formation flight is a key approach for reducing energy cost and managing traffic in future high density airspace. The use of Unmanned Aerial Vehicles (UAVs) has allowed low-budget and low-risk validation of autonomous formation flight concepts. This paper discusses the implementation and flight testing of nonlinear dynamic inversion (NLDI) controllers for close formation flight (CFF) using two distinct UAV platforms: a set of fixed wing aircraft named “Phastball” and a set of quadrotors named “NEO.” Experimental results show that autonomous CFF with approximately 5-wingspan separation is achievable with a pair of low-cost unmanned Phastball research aircraft. Simulations of the quadrotor flight also validate the design of the NLDI controller for the NEO quadrotors.


2015 ◽  
Vol 03 (01) ◽  
pp. 49-62 ◽  
Author(s):  
Marjorie Darrah ◽  
Jay Wilhelm ◽  
Thilanka Munasinghe ◽  
Kristin Duling ◽  
Steve Yokum ◽  
...  

This paper discusses the development and testing of a flexible genetic algorithm (GA)-based system used for tasking a team of unmanned aerial vehicles (UAVs) to complete a coordinated surveillance mission. The GA development, laboratory testing of the GA to ensure convergence to a "good" solution, integration testing with two ground stations, and the field testing of the algorithms are explained. The algorithm was found to be robust and flexible enough to work in various settings with different UAV types and ground stations.


Author(s):  
A.A. Moykin ◽  
◽  
A.S. Medzhibovsky ◽  
S.A. Kriushin ◽  
M.V. Seleznev ◽  
...  

Nowadays, the creation of remotely-piloted aerial vehicles for various purposes is regarded as one of the most relevant and promising trends of aircraft development. FAU "25 State Research Institute of Chemmotology of the Ministry of Defense of the Russian Federation" have studied the operation features of aircraft piston engines and developed technical requirements for motor oil for piston four-stroke UAV engines, as well as a new engine oil M-5z/20 AERO in cooperation with NPP KVALITET, LLC. Based on the complex of qualification tests, the stated operational properties of the experimental-industrial batch of M-5z/20 AERO oil are generally confirmed.


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