Abstract
ABSTRACT: The capability of navigating Unmanned Aerial Vehicles (UAVs) safely in unknown terrain offers huge potential for wider applications in non-segregated airspace. Flying in non-segregated airspace present a risk of collision with static obstacles (e.g., towers, power lines) and moving obstacles (e.g., aircraft, balloons). In this work, we propose a heuristic cascading fuzzy logic control strategy to solve for the Conflict Detection and Resolution (CD&R) problem, in which the control strategy is comprised of two cascading modules. The first one is Obstacle Avoidance control and the latter is Path Tracking control. Simulation results show that the proposed architecture effectively resolves the conflicts and achieve rapid movement towards the target waypoint.ABSTRAK: Keupayaan mengemudi Kenderaan Udara Tanpa Pemandu (UAV) dengan selamat di kawasan yang tidak diketahui menawarkan potensi yang besar untuk aplikasi yang lebih luas dalam ruang udara yang tidak terasing. Terbang di ruang udara yang tidak terasing menimbulkan risiko perlanggaran dengan halangan statik (contohnya, menara, talian kuasa) dan halangan bergerak (contohnya, pesawat udara, belon). Dalam kajian ini, kami mencadangkan satu strategi heuristik kawalan logik kabur yang melata untuk menyelesaikan masalah Pengesanan Konflik dan Penyelesaian (CD&R), di mana strategi kawalan yang terdiri daripada dua modul melata. Hasil simulasi menunjukkan bahawa seni bina yang dicadangkan berjaya menyelesaikan konflik dan mencapai penerbangan pesat ke arah titik laluan sasaran.KEYWORDS: fuzzy logic; motion planning; obstacle avoidance; path tracking; reactive navigation; UAV
Highlights
Unmanned Aerial Vehicles (UAVs) has attracted growing attention in both military and civilian applications that are considered dull, dirty or dangerous, such as intelligence, surveillance, reconnaissance, search and rescue, power line inspection, fire detection, border patrol, coastline monitoring, weather forecasts, and volcanic activity tracking [1]
Zeghal [5] conducted a survey of force field collision detection and resolution methods and Albaker [6] introduced the survey of Conflict Detection and Resolution (CD&R) methods for UAVs
Just like foot is part of the leg, and hand is part of the arm, the fuzzy control scheme is comprised of two cascading fuzzy modules that works by recursively breaking down the motion planning problem into two sub-problems, which are Obstacle Avoidance and Path Tracking
Summary
UAV has attracted growing attention in both military and civilian applications that are considered dull, dirty or dangerous, such as intelligence, surveillance, reconnaissance, search and rescue, power line inspection, fire detection, border patrol, coastline monitoring, weather forecasts, and volcanic activity tracking [1]. In order to fulfill various mission objectives, it is important to integrate intelligent control that would cause UAVs to perceive their environment and quickly to react in a reasoned manner to an unplanned situation more like a human pilot. To make scenarios sensibly pragmatic for some sort of intelligent-like behaviors for UAVs, the motion planning autonomy must be able to handle varying numbers of critical objectives under different constraints such as minimizing the path length, keeping the path as straight as possible, flying over some areas of interest, avoiding obstacles or no fly zones, and approaching the target location from a commanded direction [2]. When the UAV enters non-segregated or controlled airspace, it must have the sense and avoid capability ( referred to as collision detection and resolution systems, CD&R) to maintain safety and fluency of the air traffic. Zeghal [5] conducted a survey of force field collision detection and resolution methods and Albaker [6] introduced the survey of CD&R methods for UAVs
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