Conceptual Design and Analysis of Small Power Station for Supporting Unmanned Aerial Vehicle (UAV) Deployment

“Flight time” of unmanned aerial vehicle (UAV) or drone flying robot is the key component for supporting industrial activities. In practice, most battery-powered drones can fly 20 - 30 minutes for a single charging cycle. When the battery depleted, the drone is forced to come back to the station to recharge, or swap in a charged battery. However, these tasks are manually done by human multiple times. Aside from the inconvenience, human error and inappropriate force application may damage the socket compartment or loosen the locking system between battery and socket, making higher risk of the battery accidentally fall off from the socket during the flight. This research presents a “Small power station” to automatically load and unload battery from the drone’s mainframe with a constant force.  The station has two main functions: drone positioning, and six-slot-battery exchange mechanism. Product design and development (PDD) and Kano analysis method were applied to properly list necessary compartments of the designed station. Finite element analysis (FEA) and kinematic calculation were applied to virtually check whether or not the developed platform was designed in the safety boundary.  “DJI Matrice 100” drone was applied as the case study to demonstrate the proposed approach

Autonomous UAV Battery Swapping

One of the main hindrances of unmanned aerial vehicle (UAV) technology are power constraints. One way to alleviate some power constraints would be for two UAVs to exchange batteries while both are in flight. Autonomous mid-air battery swapping will expand the scope of UAV technology by allowing for indefinite flight times and longer missions. A single board computer will control each UAV’s flight software to respond to inputs to align with each other mid-flight. When the two UAVs have joined, mechanical components will exchange a depleted battery on the worker UAV for a freshly charged battery that belongs to the battery supply UAV. After the exchange, the drones will then detach themselves from each other, and the worker UAV will resume its mission while the battery supply UAV returns back to the ground control station

Design of a Wireless Drone Recharging Station and a Special Robot End Effector for Installation on a Power Line

Drone autonomous operations near power lines are growing steadily and require innovative techniques to keep them on air. This paper presents a novel electromechanical recharging station that can be mounted on energized AC power line to charge the drone battery wirelessly without a need to modify the electrical infrastructure. The work shows a thorough analysis of the electrical and mechanical core components to build a flexible, lightweight and efficient recharging station that can be attached to a robotic arm. The work also discusses the recharging station design and its special robot end effector that mechanically couples the station with an aerial manipulator. Finally, the recharging station has been tested in the lab and in a real power line setup to validate its design and efficiency. The total achieved mass is 2300 grams with a harvesting efficiency of 77% at 250 A primary current

Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking

The emerging massive density of human-held and machine-type nodes implies larger traffic deviatiolns in the future than we are facing today. In the future, the network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly changing traffic demands both in time and space. This flexibility cannot be achieved when the network’s infrastructure remains static. To this end, the topic of UAVs (unmanned aerial vehicles) have enabled wireless communications, and networking has received increased attention. As mentioned above, the network must serve a massive density of nodes that can be either human-held (user devices) or machine-type nodes (sensors). If we wish to properly serve these nodes and optimize their data, a proper wireless connection is fundamental. This can be achieved by using UAV-enabled communication and networks. This Special Issue addresses the many existing issues that still exist to allow UAV-enabled wireless communications and networking to be properly rolled out

Design of autonomous sustainable unmanned aerial vehicle - A novel approach to its dynamic wireless power transfer

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.Electric UAVs are presently being used widely in civilian duties such as security, surveillance, and disaster relief. The use of Unmanned Aerial Vehicle (UAV) has increased dramatically over the past years in different areas/fields such as marines, mountains, wild environments. Nowadays, there are many electric UAVs development with fast computational speed and autonomous flying has been a reality by fusing many sensors such as camera tracking sensor, obstacle avoiding sensor, radar sensor, etc. But there is one main problem still not able to overcome which is power requirement for continuous autonomous operation. When the operation needs more power, but batteries can only give for 20 to 30 mins of flight time. These types of system are not reliable for long term civilian operation because we need to recharge or replace batteries by landing the craft every time when we want to continue the operation. The large batteries also take more loads on the UAV which is also not a reliable system. To eliminate these obstacles, there should a recharging wireless power station in ground which can transmit power to these small UAVs wirelessly for long term operation. There will be camera attached in the drone to detect and hover above the Wireless Power Transfer device which got receiving and transmitting station can be use with deep learning and sensor fusion techniques for more reliable flight operations. This thesis explores the use of dynamic wireless power to transfer energy using novel rotating WPT charging technique to the UAV with improved range, endurance, and average speed by giving extra hours in the air. The hypothesis that was created has a broad application beyond UAVs. The drone autonomous charging was mostly done by detecting a rotating WPT receiver connected to main power outlet that served as a recharging platform using deep neural vision capabilities. It was the purpose of the thesis to provide an alternative to traditional self-charging systems that relies purely on static WPT method and requires little distance between the vehicle and receiver. When the UAV camera detect the WPT receiving station, it will try to align and hover using onboard sensors for best power transfer efficiency. Since this strategy relied on traditional automatic drone landing technique, but the target is rotating all the time which needs smart approaches like deep learning and sensor fusion. The simulation environment was created and tested using robot operating system on a Linux operating system using a model of the custom-made drone. Experiments on the charging of the drone confirmed that the intelligent dynamic wireless power transfer (DWPT) method worked successfully while flying on air