Detection and estimation of moving obstacles for a UAV

In recent years, research interest in Unmanned Aerial Vehicles (UAVs) has been grown rapidly because of their potential use for a wide range of applications. In this paper, we proposed a vision-based detection and position/velocity estimation of moving obstacle for a UAV. The knowledge of a moving obstacle's state, i.e., position, velocity, is essential to achieve better performance for an intelligent UAV system specially in autonomous navigation and landing tasks. The novelties are: (1) the design and implementation of a localization method using sensor fusion methodology which fuses Inertial Measurement Unit (IMU) signals and Pozyx signals; (2) The development of detection and estimation of moving obstacles method based on on-board vision system. Experimental results validate the effectiveness of the proposed approach. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved

Learning to Fly by Crashing

How do you learn to navigate an Unmanned Aerial Vehicle (UAV) and avoid obstacles? One approach is to use a small dataset collected by human experts: however, high capacity learning algorithms tend to overfit when trained with little data. An alternative is to use simulation. But the gap between simulation and real world remains large especially for perception problems. The reason most research avoids using large-scale real data is the fear of crashes! In this paper, we propose to bite the bullet and collect a dataset of crashes itself! We build a drone whose sole purpose is to crash into objects: it samples naive trajectories and crashes into random objects. We crash our drone 11,500 times to create one of the biggest UAV crash dataset. This dataset captures the different ways in which a UAV can crash. We use all this negative flying data in conjunction with positive data sampled from the same trajectories to learn a simple yet powerful policy for UAV navigation. We show that this simple self-supervised model is quite effective in navigating the UAV even in extremely cluttered environments with dynamic obstacles including humans. For supplementary video see: https://youtu.be/u151hJaGKU

Towards Flight Trials for an Autonomous UAV Emergency Landing using Machine Vision

This paper presents the evolution and status of a number of research programs focussed on developing an automated fixed wing UAV landing system. Results obtained in each of the three main areas of research as vision-based site identification, path and trajectory planning and multi-criteria decision making are presented. The results obtained provide a baseline for further refinements and constitute the starting point for the implementation of a prototype system ready for flight testing

Nonlinear State Estimation and Control of Autonomous Aerial Robots: Design and Experimental Validation of Smartphone Based Quadrotor

This work presents developments of Guidance, Navigation and Control (GNC) systems with application to autonomous Unmanned Aerial Vehicle (UAV). Precisely, this work shows the development of navigation system based on nonlinear complementary filters for position, velocity and attitude estimation using low-cost sensors. The proposed filtering method provides attitude estimates in quaternion representations and position and velocity estimates by fusing measurements from Inertial Measurement Unit (IMU), GPS, and a barometer. Least Square Method (LSM) was used in gains tuning to find the best-fitting of the estimated states with precise measurements obtained by a vision based motion capture system. A complete navigation system was produced by integrating both the attitude and the position filters. The integration of the filtering approach based primarily on the ease of design and computational load. Furthermore, the structure of the filtering design allow for straightforward implementation without a need of high performance signal processing. Moreover, the filters can be tuned totally independent of each other. This work also introduces a nonlinear flight controller for stability and trajectory tracking that is practical for real-time implementation. This controller is also demonstrated the ability of a supervisory controller to provide effective waypoint navigation capabilities in autonomous UAV. The implementation of the guidance, navigation, and control algorithms were adopted in the design of a novel smartphone based autopilot for particular quadrotor aerial platforms. The performances of the proposed work are then evaluated by means of several flight tests. The work also includes a design of advanced navigation and guidance systems based on Robot Operating System (ROS) for Search And Rescue (SAR) missions. Primarily, the performance of the navigation and guidance systems were tested in laboratory by simulating GPS measurements in Linux computer mounted on the top of a quadrotor. This activity facilitates moving by the experiments from indoor to outdoor

Development of an Emergency Radio Beacon for Small Unmanned Aerial Vehicles

Emergency locator transmitters (ELTs) used to locate manned aircrafts are not well suited to find and recover small crashed unmanned aerial vehicles (UAVs). ELTs utilize an international satellite system for search and rescue (Cospas-Sarsat System), which should leverage its expensive resources to save lives as a priority. Besides, ELTs are too big and heavy to be used within small UAVs. Some of the existing solutions for this problem are based on receivers that detect signal strength, which may be a long and tedious process not suitable for user needs. Others do not have enough range or require radio license and expensive amateur radio receivers. This paper presents an emergency radio beacon specifically designed to locate small UAVs. It is triggered automatically in the event of a crash and allows finding and recovering a crashed UAV in a fast and simple way. It meets not only the required specifications of user-friendliness, size and weight of this kind of application, but also it is a high precision and low cost device. Besides, it has enough range and endurance. The experiments carried out show the operation of the proposed system