AEROSTAT EFFECT ON UAV STABILITY

The current generation of UAVs lack extended hovering and flight capabilities. Equipping a quadrotor with an inflatable structure enhances energy efficiency. In this work, the aerostat size effect on a UAV quadrotor system is investigated, and the stability of the Lighter-than-Air system is contrasted by creating a flight dynamics model. A mathematical model of the AR DRONE 2.0 with an aerostat is formulated and simulated with Matlab in hovering mode. The mathematical model is validated by comparison to real-life flight data. A validated dynamic model describing the behavior of the drone in hovering mode was developed and used for simulation

Using distance sensors to perform collision avoidance maneuvres on UAV applications

The Unmanned Aerial Vehicles (UAV) and its applications are growing for both civilian and military purposes. The operability of an UAV proved that some tasks and operations can be done easily and at a good cost-efficiency ratio. Nowadays, an UAV can perform autonomous missions. It is very useful to certain UAV applications, such as meteorology, vigilance systems, agriculture, environment mapping and search and rescue operations. One of the biggest problems that an UAV faces is the possibility of collision with other objects in the flight area. To avoid this, an algorithm was developed and implemented in order to prevent UAV collision with other objects. “Sense and Avoid” algorithm was developed as a system for UAVs to avoid objects in collision course. This algorithm uses a Light Detection and Ranging (LiDAR), to detect objects facing the UAV in mid-flights. This light sensor is connected to an on-board hardware, Pixhawk’s flight controller, which interfaces its communications with another hardware: Raspberry Pi. Communications between Ground Control Station and UAV are made via Wi-Fi or cellular third or fourth generation (3G/4G). Some tests were made in order to evaluate the “Sense and Avoid” algorithm’s overall performance. These tests were done in two different environments: A 3D simulated environment and a real outdoor environment. Both modes worked successfully on a simulated 3D environment, and “Brake” mode on a real outdoor, proving its concepts.info:eu-repo/semantics/publishedVersio

Autonomous Obstacle Collision Avoidance System for UAVs in rescue operations

The Unmanned Aerial Vehicles (UAV) and its applications are growing for both civilian and military purposes. The operability of an UAV proved that some tasks and operations can be done easily and at a good cost-efficiency ratio. Nowadays, an UAV can perform autonomous tasks, by using waypoint mission navigation using a GPS sensor. These autonomous tasks are also called missions. It is very useful to certain UAV applications, such as meteorology, vigilance systems, agriculture, environment mapping and search and rescue operations. One of the biggest problems that an UAV faces is the possibility of collision with other objects in the flight area. This can cause damage to surrounding area structures, humans or the UAV itself. To avoid this, an algorithm was developed and implemented in order to prevent UAV collision with other objects. “Sense and Avoid” algorithm was developed as a system for UAVs to avoid objects in collision course. This algorithm uses a laser distance sensor called LiDAR (Light Detection and Ranging), to detect objects facing the UAV in mid-flights. This light sensor is connected to an on-board hardware, Pixhawk’s flight controller, which interfaces its communications with another hardware: Raspberry Pi. Communications between Ground Control Station or RC controller are made via Wi-Fi telemetry or Radio telemetry. “Sense and Avoid” algorithm has two different modes: “Brake” and “Avoid and Continue”. These modes operate in different controlling methods. “Brake” mode is used to prevent UAV collisions with objects when controlled by a human operator that is using a RC controller. “Avoid and Continue” mode works on UAV’s autonomous modes, avoiding collision with objects in sight and proceeding with the ongoing mission. In this dissertation, some tests were made in order to evaluate the “Sense and Avoid” algorithm’s overall performance. These tests were done in two different environments: A 3D simulated environment and a real outdoor environment. Both modes worked successfully on a simulated 3D environment, and “Brake” mode on a real outdoor, proving its concepts.Os veículos aéreos não tripulados (UAV) e as suas aplicações estão cada vez mais a ser utilizadas para fins civis e militares. A operacionalidade de um UAV provou que algumas tarefas e operações podem ser feitas facilmente e com uma boa relação de custo-benefício. Hoje em dia, um UAV pode executar tarefas autonomamente, usando navegação por waypoints e um sensor de GPS. Essas tarefas autónomas também são designadas de missões. As missões autónomas poderão ser usadas para diversos propósitos, tais como na meteorologia, sistemas de vigilância, agricultura, mapeamento de áreas e operações de busca e salvamento. Um dos maiores problemas que um UAV enfrenta é a possibilidade de colisão com outros objetos na área, podendo causar danos às estruturas envolventes, aos seres humanos ou ao próprio UAV. Para evitar tais ocorrências, foi desenvolvido e implementado um algoritmo para evitar a colisão de um UAV com outros objetos. O algoritmo "Sense and Avoid" foi desenvolvido como um sistema para UAVs de modo a evitar objetos em rota de colisão. Este algoritmo utiliza um sensor de distância a laser chamado LiDAR (Light Detection and Ranging), para detetar objetos que estão em frente do UAV. Este sensor é ligado a um hardware de bordo, a controladora de voo Pixhawk, que realiza as suas comunicações com outro hardware complementar: o Raspberry Pi. As comunicações entre a estação de controlo ou o operador de comando RC são feitas via telemetria Wi-Fi ou telemetria por rádio. O algoritmo "Sense and Avoid" tem dois modos diferentes: o modo "Brake" e modo "Avoid and Continue". Estes modos operam em diferentes métodos de controlo do UAV. O modo "Brake" é usado para evitar colisões com objetos quando controlado via controlador RC por um operador humano. O modo "Avoid and Continue" funciona nos modos de voo autónomos do UAV, evitando colisões com objetos à vista e prosseguindo com a missão em curso. Nesta dissertação, alguns testes foram realizados para avaliar o desempenho geral do algoritmo "Sense and Avoid". Estes testes foram realizados em dois ambientes diferentes: um ambiente de simulação em 3D e um ambiente ao ar livre. Ambos os modos obtiveram funcionaram com sucesso no ambiente de simulação 3D e o mode “Brake” no ambiente real, provando os seus conceitos

AEROSTAT EFFECT ON UAV STABILITY

The current generation of UAVs lack extended hovering and flight capabilities. Equipping a quadrotor with an inflatable structure enhances energy efficiency. In this work, the aerostat size effect on a UAV quadrotor system is investigated, and the stability of the Lighter-than-Air system is contrasted by creating a flight dynamics model. A mathematical model of the AR DRONE 2.0 with an aerostat is formulated and simulated with Matlab in hovering mode. The mathematical model is validated by comparison to real-life flight data. A validated dynamic model describing the behavior of the drone in hovering mode was developed and used for simulation

The Complete Reference (Volume 4)

This is the fourth volume of the successful series Robot Operating Systems: The Complete Reference, providing a comprehensive overview of robot operating systems (ROS), which is currently the main development framework for robotics applications, as well as the latest trends and contributed systems. The book is divided into four parts: Part 1 features two papers on navigation, discussing SLAM and path planning. Part 2 focuses on the integration of ROS into quadcopters and their control. Part 3 then discusses two emerging applications for robotics: cloud robotics, and video stabilization. Part 4 presents tools developed for ROS; the first is a practical alternative to the roslaunch system, and the second is related to penetration testing. This book is a valuable resource for ROS users and wanting to learn more about ROS capabilities and features.info:eu-repo/semantics/publishedVersio

USING DISTANCE SENSORS TO PERFORM COLLISION AVOIDANCE MANEUVRES ON UAV APPLICATIONS

The Unmanned Aerial Vehicles (UAV) and its applications are growing for both civilian and military purposes. The operability of an UAV proved that some tasks and operations can be done easily and at a good cost-efficiency ratio. Nowadays, an UAV can perform autonomous missions. It is very useful to certain UAV applications, such as meteorology, vigilance systems, agriculture, environment mapping and search and rescue operations. One of the biggest problems that an UAV faces is the possibility of collision with other objects in the flight area. To avoid this, an algorithm was developed and implemented in order to prevent UAV collision with other objects. “Sense and Avoid” algorithm was developed as a system for UAVs to avoid objects in collision course. This algorithm uses a Light Detection and Ranging (LiDAR), to detect objects facing the UAV in mid-flights. This light sensor is connected to an on-board hardware, Pixhawk’s flight controller, which interfaces its communications with another hardware: Raspberry Pi. Communications between Ground Control Station and UAV are made via Wi-Fi or cellular third or fourth generation (3G/4G). Some tests were made in order to evaluate the “Sense and Avoid” algorithm’s overall performance. These tests were done in two different environments: A 3D simulated environment and a real outdoor environment. Both modes worked successfully on a simulated 3D environment, and “Brake” mode on a real outdoor, proving its concepts.info:eu-repo/semantics/publishedVersio

SIMULASI HARDWARE IN THE LOOP UNTUK TAKE-OFF DAN LANDING OTOMATIS PADA QUADROTOR MENGGUNAKAN PIXHAWK DAN jMAVSim

The use of quadrotors in various applications has made development and research in the field of drones grow rapidly. In the research and development process, a testing phase is needed to determine the flying attitude of the quadrotor. Live testing can be risky if something goes wrong. With Hardware in The Loop Simulation, it can be used as a way to minimize the occurrence of these errors. Hardware in The Loop Simulation is a combination of software and hardware simulation. The jMAVSim simulation software is connected to the Pixhawk autopilot and ground control station. The simulation results that have been obtained make it possible to carry out direct testing on the Pixhawk autopilot. From this study, the results of the quadrotor flying attitude during take-off and landing simulations show that the quadrotor is still in a stable condition with changes in pitch and roll angles of less than 1 degree

Path Planning with Potential Field-Based Obstacle Avoidance in a 3D Environment by an Unmanned Aerial Vehicle

In this paper we address the problem of path planning in an unknown environment with an aerial robot. The main goal is to safely follow the planned trajectory by avoiding obstacles. The proposed approach is suitable for aerial vehicles equipped with 3D sensors, such as LiDARs. It performs obstacle avoidance in real time and on an on-board computer. We present a novel algorithm based on the conventional Artifcial Potential Field (APF) that corrects the planned trajectory to avoid obstacles. To this end, our modifed algorithm uses a rotation-based component to avoid local minima. The smooth trajectory following, achieved with the MPC tracker, allows us to quickly change and re-plan the UAV trajectory. Comparative experiments in simulation have shown that our approach solves local minima problems in trajectory planning and generates more effcient paths to avoid potential collisions with static obstacles compared to the original APF method