Learning-Based Multi-UAV Flocking Control With Limited Visual Field and Instinctive Repulsion

This article explores deep reinforcement learning (DRL) for the flocking control of unmanned aerial vehicle (UAV) swarms. The flocking control policy is trained using a centralized-learning-decentralized-execution (CTDE) paradigm, where a centralized critic network augmented with additional information about the entire UAV swarm is utilized...

Volumetric Pothole Detection from UAV-Based Imagery

Road networks are essential elements of a community's infrastructure and need regular inspection. Present practice requires traffic interruptions and safety risks for inspectors. The road detection system based on vehicle-mounted lasers is also quite mature, offering advantages such as high-precision defect detection, high automation, and...

Dynamic Airspace Reconfiguration with Deep Reinforcement Learning

For future operations of unmanned aviation, even higher traffic densities than previously seen in manned aviation are expected. Previous work has shown that a vertically layered airspace design performs best at improving safety metrics such as the total number of conflicts and Losses of Separation (LoSs). Furthermore, it has been shown that...

Distributed Adaptive Fixed-Time Fault-Tolerant Control for Multiple 6-DOF UAVs With Full-State Constraints Guarantee

In contrast with most existing results concerning unmanned aerial vehicles (UAVs) wherein material points or only attitude/longitudinal dynamics are considered, this article proposes a distributed fixed-time fault-tolerant control methodology for networked fixed-wing UAVs whose dynamics are six-degree-of-freedom with twelf-state-variables...

Neuromorphic computing for attitude estimation onboard quadrotors

Compelling evidence has been given for the high energy efficiency and update rates of neuromorphic processors, with performance beyond what standard Von Neumann architectures can achieve. Such promising features could be advantageous in critical embedded systems, especially in robotics. To date, the constraints inherent in robots (e.g., size...

A Novel Obstacle Detection and Avoidance Dataset for Drones

In this paper, we introduce the Obstacle Detection and Avoidance (ODA) Dataset for Drones, aiming at providing raw data obtained in a real indoor environment with sensors adapted for aerial robotics in the context of obstacle detection and avoidance. Our micro air vehicle (MAV) is equipped with the following sensors: (i) an event-based camera...

Neural network model for predicting variation in walking dynamics of pedestrians in social groups

Pedestrian spaces are increasingly becoming popular locations for shopping, recreation, festivities, and other social activities. Therefore, an improved understanding of the factors that make walking environments enjoyable and safe is essential. Most existing studies focus on modelling walking behaviours of individual pedestrians. However,...

Adaptive Vector Field Guidance Without a Priori Knowledge of Course Dynamics and Wind

The high maneuverability of fixed-wing unmanned aerial vehicles (UAVs) exposes these systems to several dynamical and parametric uncertainties, severely affecting the fidelity of modeling and causing limited guidance autonomy. This article shows enhanced autonomy via adaptation mechanisms embedded in the guidance law: a vector-field method is...

ArduPilot-Based Adaptive Autopilot: Architecture and Software-in-The-Loop Experiments

This article presents an adaptive method for ArduPilot-based autopilots of fixed-wing unmanned aerial vehicles (UAVs). ArduPilot is a popular open-source unmanned vehicle software suite. We explore how to augment the PID loops embedded inside ArduPilot with a model-free adaptive control method. The adaptive augmentation, adopted for both...

Intelligent UAV Swarm Cooperation for Multiple Targets Tracking

With the advantages of easy deployment and flexible usage, Unmanned Aerial Vehicle (UAV) has advanced the Multi-Target Tracking (MTT) applications. The UAV-MTT system has great potentials to execute dull, dangerous, and critical missions for frontier defense and security. A key challenge in UAV-MTT is how to coordinate multiple UAVs to track...

Suppression of Mainbeam Deceptive Jammer with FDA-MIMO Radar

Suppression of radar-to-radar jammers, especially the mainbeam jammers, has been an urgent demand in vehicular sensing systems with the expected increased number of vehicles equipped with radar systems. This paper deals with the suppression of mainbeam deceptive jammers with frequency diverse array (FDA)-multiple-input multiple-output (MIMO)...

A semi-physical platform for guidance and formations of fixed-wing unmanned aerial vehicles

Unmanned Aerial Vehicles (UAVs) have multi-domain applications, fixed-wing UAVs being a widely used class. Despite the ongoing research on the topics of guidance and formation control of fixed-wing UAVs, little progress is known on implementation of semi-physical validation platforms (software-in-the-loop or hardware-in-the-loop) for such...

Addressing Unmodeled Path-Following Dynamics via Adaptive Vector Field: A UAV Test Case

The actual performance of model-based path-following methods for unmanned aerial vehicles (UAVs) shows considerable dependence on the wind knowledge and on the fidelity of the dynamic model used for design. This study analyzes and demonstrates the performance of an adaptive vector field (VF) control law which can compensate for the lack of...

UAV-aided weather radar calibration

Weather radar is well recognized as an effective sensor for obtaining the microphysical and dynamical properties of precipitation at high spatial and temporal resolution. Radar calibration is one of the most important prerequisites for achieving accurate observations. In this article, a portable, cost-effective and repeatable radar calibration...

Increasing Acceptance of Tactile Feedback in UAV Teleoperations by Visualizing Force Fields

Due to the increasing complexity of controlling Unmanned Aerial Vehicles (UAVs), researchers have been trying to let automation take part of the UAV control in order to eliminate human error and reduce the workload of the operator. Such a system has been developed for UAV teleoperators which incorporates haptic feedback on the control stick...

Taxonomy of Conflict Detection and Resolution Approaches for Unmanned Aerial Vehicle in an Integrated Airspace

This paper proposes a taxonomy of Conflict Detection and Resolution (CD&R) approaches for Unmanned Aerial Vehicles (UAV) operation in an integrated airspace. Possible approaches for UAVs are surveyed and broken down based on their types of surveillance, coordination, maneuver, and autonomy. The factors are combined back selectively, with...

Metropolis: Relating airspace structure and capacity for extreme traffic densities

Personal and unmanned aerial vehicles have received increasing media attention over the last decade. As a result of the growing excitement for these two aircraft types, many within and outside the aerospace industry envision a future in which large numbers of small aircraft fly over urban areas. With this vision for the future, the question...