Unmanned aerial systems play an increasingly remarkable role in widely diffused application fields, from military defense programs and strategies to civil and commercial utilization. UAS are usually involved in dull, dirty and dangerous (DDD) scenarios, which require reliable, extended-capability, easy-to-use and cost-effective fixed-wing or rotary-wing platforms. Therefore, it is important to provide onboard systems capable of recognizing the environment around the aerial vehicle, detecting and avoiding obstacles, implementing path planning and management strategies, defining safe landing areas, and achieving full autonomy, especially for BVLOS (beyond visual line-of-sight) missions. The technical and economic challenges implied by the issues related to autonomous navigation range from hardware (sensors, platforms, controllers, etc.) to software (data processing and filtering techniques, optimal control, state estimation, innovative algorithms, etc.), and from modeling to practical realizations. The aim of this Special Issue is to seek high-quality contributions that highlight novel research results and emerging applications, addressing recent breakthroughs in UAS autonomous navigation and related fields, such as flight mechanics and control, structural design, sensor design, etc. The topics of interest include the following: - 2D and 3D mapping, target detection and obstacle avoidance; - Active perception of targets in cluttered environments (foliage, forests, etc.); - Vision-based and optical flow techniques; - Sensors and sensor fusion techniques; - Design models for guidance and controlled flight; - State estimation, data analysis and filtering techniques (KF, EKF, particle filtering, fuzzy logic, etc.); - Path planning and path management; - Optimal control and strategies (neural networks, fuzzy logic, reinforcement learning, evolutionary and genetic algorithms, AI, etc.); - Navigation in GPS-denied environments; - Autolanding and safe landing area definition (SLAD); - Environmental effects on UAVs (wind, etc.); - Autonomous UAV or MAV swarms, and distributed architectures; - BVLOS autonomous navigation.
Unmanned Aircraft Systems with Autonomous Navigation - Special Issue Reprint (Electronics MDPI)
Salvatore PonteMembro del Collaboration Group
2023
Abstract
Unmanned aerial systems play an increasingly remarkable role in widely diffused application fields, from military defense programs and strategies to civil and commercial utilization. UAS are usually involved in dull, dirty and dangerous (DDD) scenarios, which require reliable, extended-capability, easy-to-use and cost-effective fixed-wing or rotary-wing platforms. Therefore, it is important to provide onboard systems capable of recognizing the environment around the aerial vehicle, detecting and avoiding obstacles, implementing path planning and management strategies, defining safe landing areas, and achieving full autonomy, especially for BVLOS (beyond visual line-of-sight) missions. The technical and economic challenges implied by the issues related to autonomous navigation range from hardware (sensors, platforms, controllers, etc.) to software (data processing and filtering techniques, optimal control, state estimation, innovative algorithms, etc.), and from modeling to practical realizations. The aim of this Special Issue is to seek high-quality contributions that highlight novel research results and emerging applications, addressing recent breakthroughs in UAS autonomous navigation and related fields, such as flight mechanics and control, structural design, sensor design, etc. The topics of interest include the following: - 2D and 3D mapping, target detection and obstacle avoidance; - Active perception of targets in cluttered environments (foliage, forests, etc.); - Vision-based and optical flow techniques; - Sensors and sensor fusion techniques; - Design models for guidance and controlled flight; - State estimation, data analysis and filtering techniques (KF, EKF, particle filtering, fuzzy logic, etc.); - Path planning and path management; - Optimal control and strategies (neural networks, fuzzy logic, reinforcement learning, evolutionary and genetic algorithms, AI, etc.); - Navigation in GPS-denied environments; - Autolanding and safe landing area definition (SLAD); - Environmental effects on UAVs (wind, etc.); - Autonomous UAV or MAV swarms, and distributed architectures; - BVLOS autonomous navigation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
