Collision Avoidance of Hexacopter UAV Based on LiDAR Data in Dynamic Environment

Priority-Aware Conflict Resolution for U-Space

In the context of the future urban mobility airspaces, U-space lays the foundation for unmanned aircrafts to be integrated with conventionally manned traffic to offer a multitude of services to citizens and businesses, such as urban public transport, goods movement, parcel delivery, etc. Given these extensive possibilities, it is estimated that thousands of aircrafts (or even more) from different owners will share common airspace volumes, and the probability that all of them will travel without colliding is extremely low if no means are put in place to prevent it. This paper aims to introduce the reader to the conflict management policy proposed in U-space and proposes a new version of the PCAN (Prediction-based Conflict-free Adaptive Navigation) algorithm to adapt to this policy. In particular, the new implementation of PCAN takes into account a more than likely classification of flights according to their priority. The evaluation of this priority-aware algorithm shows that it is still possible to avoid any conflict between the set of aircraft in flight, with an insignificant detriment to higher priority flights, while maintaining minimal detriment on average.

The Improved A* Obstacle Avoidance Algorithm for the Plant Protection UAV with Millimeter Wave Radar and Monocular Camera Data Fusion

To enhance obstacle avoidance abilities of the plant protection UAV in unstructured farmland, this article improved the traditional A* algorithms through dynamic heuristic functions, search point optimization, and inflection point optimization based on millimeter wave radar and monocular camera data fusion. Obstacle information extraction experiments were carried out. The performance between the improved algorithm and traditional algorithm was compared. Additionally, obstacle avoidance experiments were also carried out. The results show that the maximum error in distance measurement of data fusion method was 8.2%. Additionally, the maximum error in obstacle width and height measurement were 27.3% and 18.5%, respectively. The improved algorithm is more useful in path planning, significantly reduces data processing time, search grid, and turning points. The algorithm at most increases path length by 2.0%, at least reduces data processing time by 68.4%, search grid by 74.9%, and turning points by 20.7%. The maximum trajectory offset error was proportional to the flight speed, with a maximum trajectory offset of 1.4 m. The distance between the UAV and obstacle was inversely proportional to flight speed, with a minimum distance of 1.6 m. This method can provide a new idea for obstacle avoidance of the plant protection UAV.

A Tactical Conflict Resolution Proposal for U-Space Zu Airspace Volumes

Conflict management between UAVs is one of the key aspects in developing future urban aerial mobility (UAM) spaces, such as the one proposed in U-Space. In the framework of tactical conflict management, i.e., with the UAVs in flight, this paper presents PCAN (Prediction-based Conflict-free Adaptive Navigation). This relatively simple navigation technique predicts the occurrence of the conflict and avoids it by modifying the velocity vector of the UAVs involved. The performance evaluation carried out demonstrates its effectiveness compared to similar techniques, even in high-density scenarios, while proving a low overhead in flight time or in the distance traveled by the UAVs to reach their destinations.

A Modular Multirotor Unmanned Aerial Vehicle Design Approach for Development of an Engineering Education Platform

The development of multirotor unmanned aerial vehicles (UAVs) has enabled a vast number of applications. Since further market growth is expected in the future it is important that modern engineers be familiar with these types of mechatronic systems. In this paper, a comprehensive mathematical description of a multirotor UAV, with various configuration parameters, is given. A modular design approach for the development of an educational multirotor platform is proposed. Through the stages of computer-aided design and rapid prototyping an experimental modular multirotor (EMMR) platform is presented. Open-source control system and a novel EMMR enable students to create and test control algorithms for various multirotor configurations. The presented EMMR platform is suitable for students to expand their educational objectives in aerial robotics and control theory.

Method for Characterization of a Multirotor UAV Electric Propulsion System

Due to their abilities, multirotor unmanned aerial vehicles (UAVs) can be used in various missions that require complex and precise movements, so they are a typical representative of aerial robots. Since this type of UAV is characterized by high energy consumption, it is of most importance to precisely choose the system parameters and components in order to achieve the required flight performance that meets the mission requirements. In this paper, a method for characterization of the multirotor UAV propulsion system is proposed, which is a fundamental step in the design process of this type of UAV. For the purpose of method validation, experimental measurements and signal acquisition were performed, and the measurement results for the considered electric propulsion units were shown. An identification procedure is presented, which is used to process the measurement results or manufacturer’s data and display them as propulsion unit static maps. Based on static maps, the characterization process of the electric propulsion system is performed, and the propulsion unit characteristics are shown.