There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Classifications, applications, and design challenges of drones: A review

Proceedings of the fifth annual workshop on Computational learning theory

Nowadays, Unmanned Aerial Vehicles (UAVs) are used in many different applications. Using systems of multiple UAVs is the next obvious step in the process of applying this technology for variety of ...

https://www.worldscientific.com/doi/pdf/10.1142/S2301385020500090

Multiple UAV Systems: A Survey

Micro- and nano air vehicles are defined as “extremely small and ultra-lightweight air vehicle systems” with a maximum wingspan length of 15 cm and a weight less than 20 grams. Here, we provide a review of the current state of the art and identify the challenges of design and fabrication. Different configurations are evaluated, such as fixed wings, rotary wings, and flapping wings. The main advantages and drawbacks for each typology are identified and discussed. Special attention is given to rotary-wing vehicles (helicopter concept); including a review of their main structures, such as the airframe, energy storage, controls, and communications systems. In addition, a review of relevant sensors is also included. Examples of existing and future systems are also included. Micro- and nano-vehicles with rotary wings and rechargeable batteries are dominating. The flight times of current systems are typically around 1 hour or less due to the limited energy storage capabilities of the used rechargeable batteries. Fuel cells and ultra capacitors are promising alternative energy supply technologies for the future. Technology improvements, mainly based on micro- and nanotechnologies, are expected to continue in an evolutionary way to improve the capabilities of future micro- and nano air vehicles, giving improved flight times and payload capabilities.

/pdf/micro-and-nano-air-vehicles-state-of-the-art-4bdbqcldt3.pdf

Micro- and Nano-Air Vehicles: State of the Art

T his paper focuses on the quadrotor drag coefficient model and its estimation from flight tests. Precise assessment of such

Evaluation of drag coeﬀicient for a quadrotor model

/pdf/experimental-verification-of-a-semi-empirical-v-stol-5cje4pbfbo.pdf

Experimental Verification of a Semi-Empirical V/STOL Aircraft Performance Analysis Method

Aircraft runways are periodically inspected for debris and damage. Instead of having pilots coordinate the motion of the quadrotors manually or hand-crafting the desired quadrotor behavior into a guidance law, this paper reports the use of deep reinforcement learning to learn a closed-loop multiagent real-time guidance strategy for quadrotors to autonomously perform such inspections. This yields a significant reduction in engineering effort while enabling highly-flexible real-time performance. The runway is discretized into a number of rectangular tiles, which must all be visited for the runway to be considered inspected. The guidance system reported here calculates a desired acceleration in real time for the quadrotor(s) to track in order to complete the task. This paper first develops the guidance technique, trains it in simulation, and evaluates it experimentally using an indoor quadrotor laboratory. This process is then repeated for an outdoor setting on a real runway, where the proposed guidance strategy is compared to a handcrafted strategy and applied to a multiquadrotor scenario where the quadrotors must learn to coordinate their behavior and be resilient to the failure of one quadrotor mid-experiment. Multiagent, fault-tolerant, learned behavior is successfully demonstrated through outdoor quadrotor flights. Additional simulations and experiments demonstrate the technique is viable in a swarm with additional quadrotors, on a variety of runway shapes and with increased discretization of the runway. This work shows how modern learning-based techniques can: 1) reduce the engineering effort required to design complex guidance systems and 2) be implemented on real hardware in a representative outdoor environment.

/pdf/learned-multiagent-real-time-guidance-with-applications-to-l3n73at9.pdf

Murat Bronz

Papers

Evaluation of drag coeﬀicient for a quadrotor model

Experimental Verification of a Semi-Empirical V/STOL Aircraft Performance Analysis Method

Learned Multiagent Real-Time Guidance with Applications to Quadrotor Runway Inspection