Related papers: FlowDrone: Wind Estimation and Gust Rejection on U…
Real-time high-resolution wind predictions are beneficial for various applications including safe manned and unmanned aviation. Current weather models require too much compute and lack the necessary predictive capabilities as they are valid…
Understanding airflow around a drone is critical for performing advanced maneuvers while maintaining flight stability. Recent research has worked to understand this flow by employing 2D and 3D flow sensors to measure flow from a single…
Real-time altitude control of airborne wind energy (AWE) systems can improve performance by allowing turbines to track favorable wind speeds across a range of operating altitudes. The current work explores the performance implications of…
Experimental assessment of safe and precise flight control algorithms for unmanned aerial vehicles (UAVs) under gusty wind conditions requires the capability to generate a large range of velocity profiles. In this study, we employ a small…
The research presents an automated method for determining the trajectory of an unmanned aerial vehicle (UAV) for wind turbine inspection. The proposed method enables efficient data collection from multiple wind installations using UAV…
To enable autonomous wind estimation for energy-efficient flight in small unmanned aerial vehicles (UAVs), this study proposes a method that estimates flight states and wind using only the low-cost essential onboard sensors required for…
Automatic detection of flying drones is a key issue where its presence, especially if unauthorized, can create risky situations or compromise security. Here, we design and evaluate a multi-sensor drone detection system. In conjunction with…
The use of drones in a wide range of applications is steadily increasing. However, this has also raised critical security concerns such as unauthorized drone intrusions into restricted zones. Therefore, robust and accurate drone detection…
Advanced technological breakthroughs and exceptional levels of innovation are enhancing the capabilities and potential of autonomous unmanned aerial vehicles (UAVs or drones), and in so doing attracting the interest of a broader swath of…
In precision agriculture and plant science, there is an increasing demand for wireless sensors that are easy to deploy, maintain, and monitor. This paper investigates a novel approach that leverages recent advances in extremely low-power…
Traffic forecasting is a fundamental task in transportation research, however the scope of current research has mainly focused on a single data modality of loop detectors. Recently, the advances in Artificial Intelligence and drone…
This study evaluates pilots' cognitive workload and situational awareness during remote small unmanned aircraft system operations in different wind conditions. To complement the urban air mobility concept that envisions safe, sustainable,…
Wind power generation plays a crucial role in transitioning away from fossil fuel-dependent energy sources, contributing significantly to the mitigation of climate change. Monitoring and evaluating the aerodynamics of large wind turbine…
The development of safe and reliable autonomous unmanned aerial vehicles relies on the ability of the system to recognise and adapt to changes in the local environment based on sensor inputs. State-of-the-art local tracking and trajectory…
This work demonstrates an airflow inertial based odometry system with multi-sensor data fusion, including thermal anemometer, IMU, ESC, and barometer. This goal is challenging because low-cost IMUs and barometers have significant bias, and…
Drone-based rapid and accurate environmental edge detection is highly advantageous for tasks such as disaster relief and autonomous navigation. Current methods, using radars or cameras, raise deployment costs and burden lightweight drones…
In this work we demonstrate the possibility of estimating the wind environment of a UAV without specialised sensors, using only the UAV's trajectory, applying a causal machine learning approach. We implement the causal curiosity method…
With the increase in use of Unmanned Aerial Vehicles (UAVs)/drones, it is important to detect and identify causes of failure in real time for proper recovery from a potential crash-like scenario or post incident forensics analysis. The…
Accurately estimating risk in real-time is essential for ensuring the safety and efficiency of many applications involving autonomous robot systems. This paper presents a novel, generalizable algorithm for the real-time estimation of risks…
Autonomous drone navigation faces a critical challenge in achieving accurate landings on dynamic platforms, especially under unpredictable conditions such as wind turbulence. Our research introduces TornadoDrone, a novel Deep Reinforcement…