Artificial Intelligence Applications for Drones Navigation in GPS-denied or degraded Environments

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A Bioinspired Neural Network-Based Approach for Cooperative Coverage Planning of UAVs

This paper describes a bioinspired neural-network-based approach to solve a coverage planning problem for a fleet of Unmanned Aerial Vehicles exploring critical areas. The main goal is to fully cover the map, maintaining a uniform distribution of the fleet on the map, and avoiding collisions between vehicles and other obstacles. This specific task is suitable for surveillance applications, where the uniform distribution of the fleet in the map permits them to reach any position on the map as fast as possible in emergency scenarios. To solve this problem, a bioinspired neural network structure is adopted. Specifically, the neural network consists of a grid of neurons, where each neuron has a local cost and has a local connection only with neighbor neurons. The cost of each neuron influences the cost of its neighbors, generating an attractive contribution to unvisited neurons. We introduce several controls and precautions to minimize the risk of collisions and optimize coverage planning. Then, preliminary simulations are performed in different scenarios by testing the algorithm in four maps and with fleets consisting of 3 to 10 vehicles. Results confirm the ability of the proposed approach to manage and coordinate the fleet providing the full coverage of the map in every tested scenario, avoiding collisions between vehicles, and uniformly distributing the fleet on the map

Implementation of a Comprehensive Mathematical Model for Tilt-Rotor Real-Time Flight Simulation

This paper aims at describing the effort performed by the joint research group of Politecnico di Torino and ZHAW (Zurich University of Applied Sciences) in achieving a novel implementation of a mathematical model for real-time flight simulation of tilt-rotors and tilt-wings aircraft. The focus is on the description of the current stage of the project, the achievements of the first version of the model, on-going improvements and future developments. The first part of the work describes the initial development of the overall simulation model: relying on several NASA reports on the Generic Tilt Rotor Simulator (GTRS), the mathematical model is revised and the rotor dynamic model is improved in order to enhance computational performance. In particular, the model uses the conventional mathematical formulation for non-dynamic inflow modelling based on Blade Element Momentum Theory. A novel but simple numerical method is used to ensure the convergence of the non-linear equation in every tested condition. The resulting simulation model and its development and implementation in the MATLAB/Simulink® environment is described. The second part of the work deals with the integration of the model in the ZHAW Research and Didactics Simulator (ReDSim), the replacement of the pilot controls by the introduction of a center stick and the corresponding adjustment of the force-feel system to suitable values for the tilt-rotor model. Subsequently, several pilot tests are carried out and preliminary feedbacks about the overall behaviour of the system are collected. Limits and weaknesses of the first release of the model are investigated and future necessary improvements are assessed, such as the development of a novel generic prop-rotor mathematical model. The third part introduces the novel multi-purpose rotor mathematical model which was developed to improve the overall tilt-rotor simulation model. The multi-purpose rotor model implements non-approximated flapping dynamics and inflow dynamic based on Pitt-Peters formulation. The validation of the novel rotor model is carried out with available data of both the XV-15 Research Aircraft and the UH-60 Helicopter

Autonomous Drones in GNSS-Denied Environments: Results from the Leonardo Drone Contest

The Leonardo Drone Contest is an autonomous drone competition that aims at finding innovative solutions for drones operating in a Global Navigation Satellite System (GNSS) denied environment. At the end of a three years cycle of the competition, in this paper a review of the identified system and conclusions made by the DRAFT team from Politecnico di Torino is presented. The authors aim at introducing the final solutions to the challenge in terms of hardware components, algorithms and development process. The proposed approach has been widely tested and validated, and it ranked second in the competition. The well-consolidated procedure, resulting from many iterations in the development cycle, has contributed to further improvements during the three-year challenge and can be helpful for anyone who desires to approach the problem of autonomous drones employed in smart cities contexts

Implementation of a comprehensive mathematical model for tilt-rotor real-time flight simulation

This paper aims at describing the effort performed by the joint research group of Politecnico di Torino and ZHAW (Zurich University of Applied Sciences) in achieving a novel implementation of a mathematical model for real-time flight simulation of tilt-rotors and tilt-wings aircraft. The focus is on the description of the current stage of the project, the achievements of the first version of the model, on-going improvements and future developments. The first part of the work describes the initial development of the overall simulation model: relying on several NASA reports on the Generic Tilt Rotor Simulator (GTRS), the mathematical model is revised and the rotor dynamic model is improved in order to enhance computational performance. In particular, the model uses the conventional mathematical formulation for non-dynamic inflow modelling based on Blade Element Momentum Theory. A novel but simple numerical method is used to ensure the convergence of the non-linear equation in every tested condition. The resulting simulation model and its development and implementation in the MATLAB/Simulink® environment is described. The second part of the work deals with the integration of the model in the ZHAW Research and Didactics Simulator (ReDSim), the replacement of the pilot controls by the introduction of a center stick and the corresponding adjustment of the force-feel system to suitable values for the tilt-rotor model. Subsequently, several pilot tests are carried out and preliminary feedbacks about the overall behaviour of the system are collected. Limits and weaknesses of the first release of the model are investigated and future necessary improvements are assessed, such as the development of a novel generic prop-rotor mathematical model. The third part introduces the novel multi-purpose rotor mathematical model which was developed to improve the overall tilt-rotor simulation model. The multi-purpose rotor model implements non-approximated flapping dynamics and inflow dynamic based on Pitt-Peters formulation. The validation of the nover rotor model is carried out with available data of both the XV-15 Research Aircraft and the UH-60 Helicopter

Implementation of a comprehensive real-time flight simulator for XV-15 tilt-rotor aircraft

This paper presents a tilt-rotor flight simulation platform implementing a real-time simulation of the Bell XV-15 aircraft for teaching and research purposes. The mathematical model of the tilt-rotor aircraft is implemented in MATLAB/Simulink© including simplified models of aircraft dynamics, actuators, sensors, and Flight Control Computer. The implemented tilt-rotor mathematical model is interfaced with flight control hardware, i.e. a flight stick and a rudder pedal, used by the pilot to set input commands. Instead, the graphics environment is provided by FlightGear, an open-source and cross-platform software widely used in research activities. Another contribution of the paper is the design and implementation of a Stability Control and Augmentation System to enhance aircraft stability and improve handling qualities. The developed simulator is tested with several simulations validating the developed mathematical model and the effectiveness of the Stability Control and Augmentation System. The result is a tilt-rotor flight simulation platform executable on a commercial laptop with real-time performance for research and teaching activities

Reinforcement Learning based Coverage Planning for UAVs Fleets

This paper proposes a Reinforcement Learning (RL) approach for coverage planning of unexplored areas with obstacles applied to fleets of Unmanned Aerial Vehicles (UAVs) . The goal is to reduce the steps and the energy needed to achieve full coverage, while avoiding collisions with fixed obstacles and other fleet members. This objective is accomplished through a Reinforcement Learning (RL)-based algorithm, through which UAVs are trained concurrently in simulated environment to maximize their individually explored areas while keeping uniformly distributed. This mixed cooperative-competitive behaviour is learned through a Convolutional Neural Network (CNN), running on each fleet unit, which outputs a suitable waypoint to be reached on the basis of all UAVs locations and already explored areas. Training process is developed in a novel approach, by gathering all UAVs’ trajectories collected during simulated episodes to update a shared policy function. In test phase, the learned behaviour is exploited in a decentralized way. Trained fleets are tested in simulated fields with different obstacle configurations, and performances are assessed in terms of both strategical distribution and exploration capabilities in maps with different complexity levels. Results show that fleets of 2 to 10 drones manage to reach full coverage of the test maps while spreading efficiently in the environment

Resolution and Frequency Effects on UAVs Semi-Direct Visual-Inertial Odometry (SVO) for Warehouse Logistics

For the commercial sector, warehouses are becoming increasingly vital. Constant efforts are in progress to increase the efficiency of these facilities while reducing costs. The inventory part of the goods is a time-consuming task that impacts the company’s revenue. This article presents an analysis of the performance of a state-of-the-art, visual-inertial odometry algorithm, SVO Pro Open, when varying the resolution and frequency of video streaming in an industrial environment. To perform efficiently this task, achieving an optimal system in terms of localization accuracy, robustness, and computational cost is necessary. Different resolutions are selected with a constant aspect ratio, and an accurate calibration for each resolution configuration is performed. A stable operating point in terms of robustness, accuracy of localization, and CPU utilization is found and the trends obtained are studied. To keep the system robust against sudden divergence, the feature loss factor extracted from optical sensors is analyzed. Innovative trends and translation errors on the order of a few tens of centimeters are achieved, allowing the system to navigate safely in the warehouse. The best result is obtained at a resolution of 636 × 600 px, where the localization errors (x, y, and z) are all under 0.25 m. In addition, the CPU (Central Processing Unit) usage of the onboard computer is kept below 60%, remaining usable for other relevant onboard processing tasks

Commento agli articoli 75-81 c.p.c., Delle parti, in Codice di procedura civile. Commentario diretto da Claudio Consolo. Vol. 1

Commento sistematico agli articoli da 75 a 81 del c.p.c. alla luce delle interpretazioni dottrinali e degli orientamenti giurisprudenzial