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Multirotors are gaining great importance in the layout of innovative and more agile mobility. In this framework, a possible solution to developing an aircraft complying with the stringent size requirements characterizing this type of application may be a coaxial rotor configuration. To exploit several possibilities linked to coaxial rotors, a scaled experimental model is designed to evaluate the performances of the counter-rotating propeller system, specifically regarding the distance between the two propellers. Both thrust and noise are considered as parameters of interest. Two brushless motors are deployed, whereas the propellers’ angular velocity, in terms of rounds per minute (rpm), is controlled by an external control system. Tests are conducted on both single isolated propellers as well as on the counter-rotating system: the two propellers and their respective motors are characterized regarding the thrust. Furthermore, a comparison with a numerical model is performed. Noise evaluation on the single propeller shows a motor contribution prevalence at a low rpm range (1140–1500 rpm) and a propeller prevalence for angular velocities higher than 1860 rpm. By varying the distances between the propellers, a sensitivity analysis is performed with the aim of identifying the optimum configuration, taking into account both noise and thrust performances.

In recent years, artificial neural networks (ANNs) have completely changed the field of machine learning, especially computer vision. The Spike Neural Network (SNN) is biologically more realistic than ANN. It is more hardware-friendly and energy-efficient, and suitable for running on portable devices with weak computing performance. In this paper we aim to classify several Chinese character images based on SNN. The input image is preprocessed by traditional methods (OpenCV) and then it is input into the trained spike neural network to classify the characters. Different hyperparameters configurations are tested reaching an optimal configuration and a classification accuracy rate of 93%.

Multirotors are gaining great importance in the layout of innovative and more agile mobility. In this framework, a possible solution to developing an aircraft complying with the stringent size requirements characterizing this type of application can be a coaxial rotor configuration. To exploit the several possibilities linked to coaxial rotors, a scaled experimental model is designed to evaluate the performances of the counter-rotating propellers system, concerning the distance between the two propellers. Both thrust and noise are considered as parameters of interest. Two brushless motors are deployed whereas the propellers' angular velocity, in terms of round per minute (rpm), is controlled by an external control system. Tests are conducted on both single isolated propellers as well as on the counter-rotating system: the two propellers and their respective motors have been characterized concerning the thrust. Furthermore, a comparison with a numerical model is performed. Noise evaluation on the single propeller has shown a motor contribution prevalence at a low rpm regime (1140-1500 rpm) and a propeller prevalence for angular velocities higher than 1860 rpm. By varying the distances between the propellers a sensitivity analysis is performed with the aim of identifying the optimum configuration taking into account both noise and thrust performances.

Neuromorphic computing is going to be the new standard in low power AI applications. The integration between new neuromorphic hardware and traditional microcontroller is an open challenge. Here we present an interface board and a communication protocol that allows the communication between different devices using a microcontroller unit (Arduino Due) in the middle. Our compact printed circuit board (PCB) board links different devices as a whole system and provides power supply for the entire system using batteries as power source. Specifically, we have connected a Dynamic Vision Sensor (DVS128), SpiNNaker board and a servo motor, creating a platform for intercepting incoming objects. The data rate of the implemented interface board is 24.64k symbols/s and the latency for generating commands is about 11ms. The complete system is run only by batteries making it very suitable for robotic applications.