scholarly journals The Design of Prometheus: A Reconfigurable UAV for Subterranean Mine Inspection

Robotics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 95
Author(s):  
Liam Brown ◽  
Robert Clarke ◽  
Ali Akbari ◽  
Ujjar Bhandari ◽  
Sara Bernardini ◽  
...  
Keyword(s):  
Autonomous Robot ◽  
Traditional Methods ◽  
Discrete Sampling ◽  
Full Coverage ◽  
Aerial Vehicles ◽  
Difficult Time ◽  
Mine Workings ◽  
Autonomous Aerial Vehicles ◽  
Intelligent Controllers ◽  
Paper Address

The inspection of legacy mine workings is a difficult, time consuming, costly task, as traditional methods require multiple boreholes to be drilled to allow sensors to be placed in the voids. Discrete sampling of the void from static locations also means that full coverage of the area cannot be achieved and occluded areas and side tunnels may not be fully mapped. The aim of the Prometheus project is to develop an autonomous robotic solution that is able to inspect the mine workings from a single borehole. This paper presents the challenges of operating autonomous aerial vehicles in such an environment, as well as physically entering the void with an autonomous robot. The paper address how some of these challenges can be overcome with bespoke design and intelligent controllers. It details the design of a reconfigurable UAV that is able to be deployed through a 150 mm borehole and unfold to a tip-to-tip diameter of 780 mm, allowing it to carry a payload suitable for a full autonomous mission.

Vehicle Health Inferencing Using Feature-Based Neural-Symbolic Networks

2013 ◽  
Author(s):  
Christopher M. Aasted ◽  
Sunwook Lim ◽  
Rahmat A. Shoureshi
Keyword(s):  
Historical Data ◽  
Fault Tolerant ◽  
Current System ◽  
Diagnostic Information ◽  
Aerial Vehicles ◽  
Feature Based ◽  
Incident Data ◽  
Autonomous Aerial Vehicles ◽  
Diagnostics System

In order to optimize the use of fault tolerant controllers for unmanned or autonomous aerial vehicles, a health diagnostics system is being developed. To autonomously determine the effect of damage on global vehicle health, a feature-based neural-symbolic network is utilized to infer vehicle health using historical data. Our current system is able to accurately characterize the extent of vehicle damage with 99.2% accuracy when tested on prior incident data. Based on the results of this work, neural-symbolic networks appear to be a useful tool for diagnosis of global vehicle health based on features of subsystem diagnostic information.

scholarly journals Distributed Control of Networked Unmanned Aerial Vehicles for Valley Area Coverage

2016 ◽  
Vol 2016 ◽  
pp. 1-12
Author(s):  
Mengji Shi ◽  
Kaiyu Qin
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Distributed Control ◽  
A Priori ◽  
Future Research ◽  
Control Law ◽  
Full Coverage ◽  
Aerial Vehicles ◽  
Crash Avoidance ◽  
Pass Through ◽  
Valley Area

The paper provides a novel cooperative motion scheme for networked Unmanned Aerial Vehicles (UAVs) to fully sweep-cover a priori unknown elongated areas with curved borders, which are termed “valley areas.” The UAVs’ motion is confined between the borders. Different from former research on straight-corridor-sweep-coverage, in each valley area, the width of different portions varies dramatically: the UAVs need to line up across the valley area to achieve full coverage of the widest portions while they can only pass through the narrowest parts one by one in a queue. The UAVs are provided with barrier detection and inter-UAV communication. According to the scheme, a distributed control law has been offered for discrete-time multi-UAV systems, guaranteeing crash avoidance and full coverage while considering the constrained mobility of the UAVs. Regular and extreme simulations are carried out to verify the efficacy and stability of the proposed algorithm. Solutions to U-shaped valley coverage and the case of insufficient UAVs available are discussed with validation simulations. Comparison simulations are conducted with respect to a line-sweep-coverage algorithm developed by a closely related work, and differences in performance are revealed subsequently. Conclusions are drawn with possible directions of future research.

ANALYSIS OF THE STATE OF THE PROVISION OF DRONES THAT WERE CREATED DURING THE COURSE OF THE ANTI-TERRORIST OPERATION IN THE EAST OF UKRAINE

2019 ◽  
pp. 29-35
Author(s):  
R. Koltsov ◽  
P. Vaniyev ◽  
D. Indutniy
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Armed Forces ◽  
The State ◽  
Special Forces ◽  
Traditional Methods ◽  
Aerial Vehicles ◽  
Starting Point ◽  
Guidance Documents ◽  
Effective Use ◽  
Source Materials

The article presents the analysis of unmanned aerial vehicles that were created during the conduct of the anti-terrorist operation in eastern Ukraine. The article is based on the description of the features of the use of unmanned aerial vehicles in eastern Ukraine. The article also discusses the advantages of using unmanned aerial vehicles when performing combat missions. The leading concepts of creating unmanned aerial vehicles and a set of factors that determine the success of providing unmanned aerial vehicles with the Armed Forces of Ukraine are defined. The experience of using and providing unmanned aerial vehicles and unmanned aviation complexes during anti-terrorist operation in eastern Ukraine was generalized. Ways to improve the traditional methods of creating unmanned aerial vehicles and identify for which tasks unmanned aerial vehicles were used during the anti-terrorist operation. The article describes the types of unmanned aerial complexes used in the area of anti-terrorist operation by Ukrainian military, special forces and guards. As a result of the research the peculiarities of determining operational-tactical requirements for unmanned aerial vehicles for their effective use in the east of Ukraine are revealed. The rational ways of creation of unmanned aerial vehicles for their use in the interests of combat use are offered. The starting point for the analysis was some recent publications on the creation and use of drones for military purposes and guidance documents. The source materials were checked for compliance with the criteria set out in the guidance documents.

scholarly journals Robust detection of small and dense objects in images from autonomous aerial vehicles

2021 ◽  
Author(s):  
Joo Chan Lee ◽  
JeongYeop Yoo ◽  
Yongwoo Kim ◽  
SungTae Moon ◽  
Jong Hwan Ko
Keyword(s):  
Robust Detection ◽  
Aerial Vehicles ◽  
Autonomous Aerial Vehicles
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