Collision Avoidance For Unmanned Aerial Vehicles Research Articles

非隔离空域无人机防撞需求初探

数量剧增的无人机迫切需要与普通航空器共享非隔离空域资源，给本已十分繁忙的空中交通带来了安全隐患。由于在法规、通信、监视、可靠性和感知防撞方面，无人机尚未达到与有人机同样的安全水平，使无人机系统被有效整合进非隔离空域，成为各国航管组织亟待解决的重要问题。基于无人机防撞原理及非隔离空域类型，充分考虑空域威胁目标属性，制定无人机防撞需求标准，为无人机防撞系统的研制及相关空管标准规范的制定提供依据。 The increasing number of unmanned aerial vehicles is urgently needed to share non-isolated airspace resources with ordinary aircrafts, which poses a potential safety hazard to already busy air traffic. UAVs have not yet reached the same level of safety as manned aircraft in terms of regulations, communications, surveillance, reliability and perceptual collision avoidance, making UAVs effectively integrated into non-segregated airspace and becoming an urgent problem to be addressed by national air traffic control organizations. Based on the principles of unmanned aerial vehicles collision avoidance and the types of non-isolated airspace, this paper takes the airspace threat target attribute into consideration, and establishes the anti-collision requirement standard for unmanned aerial vehicles and provides basis for the development of unmanned aerial vehicle collision avoidance system and relevant air traffic control standards.

Reactive Collision Avoidance of UAVs with Simple Pin-hole Camera Based Passive Stereovision Sensing

An effective reactive collision avoidance algorithm is presented in this paper for unmanned aerial vehicles (UAVs) using two simple inexpensive pinhole cameras. The vision sensed data, which consists of the azimuth and elevation angles at the two camera positions, is first processed through a Kalman filter formulation to estimate the position and velocity of the obstacle. Once the obstacle position is estimated, the collision cone philosophy is used to predict the collision over a short period of time. In case a collision is predicted, steering guidance commands are issued to the vehicle to steer its velocity vector away using the nonlinear differential geometric guidance. A new cubic spline based post-avoidance merging algorithm is also presented so that the vehicle rejoins the intended global path quickly in a smooth manner after avoiding the obstacle. The overall algorithm has been validated using the point mass model of a prototype UAV with first-order autopilot delay. Both extended Kalman filtering (EKF) and unscented Kalman filtering (UKF) have been experimented. Both are found to be quite effective. However, performance of UKF was found to be better than EKF with minor compromise in computational efficiency and hence it can be a better choice. Note that because of two cameras, stereovision signature gets associated with optical flow signature thereby making the overall signature quite strong for obstacle position estimation. This leads to a good amount of success as compared to the usage of a single pinhole camera, results of which has been published earlier.

A symbiotic simulation architecture for evaluating UAVs collision avoidance techniques

Unmanned aerial vehicles (UAVs) currently have many real-world applications such as surveying, delivering small packages, and military applications. In order to maintain safe flight, UAVs require collision avoidance to divert them from collisions or other known dangerous paths. Many algorithms have been developed and implemented, but seldom are they compared to each other analytically within a single system. In this paper, an implementation of a symbiotic simulation architecture is described to conduct cyber-physical experiments and to allow different collision avoidance algorithms to be tested in real-time. Three algorithms based on mixed-integer linear programming (MILP), sparse A* search, and artificial potential fields (APF) are implemented, and results of computational experiments are presented. MILP provides the most efficient paths when given enough time. A* and APF exhibit similar performance, with APF being the least computing expensive. On the basis of the results of the experiments, three hybrid algorithms are proposed for future tests using the embedded simulation architecture.

UAV-borne X-band radar for collision avoidance

SUMMARYThe increased use of unmanned aerial vehicles (UAVs) is coincidentally accompanied by a notable lack of sensors suitable for enabling further improvement in levels of autonomy and, consequently, integration into the National Airspace System (NAS). The majority of available sensors suitable for UAV integration into the NAS are based on infrared detectors, focal plane arrays, optical and ultrasonic rangefinders, etc. These sensors are generally not able to detect or identify other UAV-sized targets and, when detection is possible, considerable computational power is typically required for successful identification. Furthermore, the performance of visual-range optical sensor systems may suffer when operating under conditions that are typically encountered during search and rescue, surveillance, combat, and most other common UAV applications. However, the addition of a miniature RADAR sensor can, in consort with other sensors, provide comprehensive target detection and identification capabilities for UAVs. This trend is observed in manned aviation where RADAR sensors are the primary on-board detection and identification sensors. In this paper, a miniature, lightweight X-band RADAR sensor for use on a miniature (710-mm rotor diameter) rotorcraft is described. We present an analysis of the performance of the RADAR sensor in a realistic scenario with two UAVs. Additionally, an analysis of UAV navigation and collision avoidance behaviors is performed to determine the effect of integrating RADAR sensors into UAVs. Further study is also performed to demonstrate the scalability of the RADAR for use with larger UAV classes.

UNMANNED AERIAL VEHICLE COLLISION AVOIDANCE USING DIGITAL ELEVATION MODEL

In the article the important role of Digital Elevation Models for Unmanned Aerial Vehicle collision avoidance and flight planning have been discussed. The web sources of Digital Elevation Models with their descriptions and data transformation procedure for the further processing were represented. The principle of the collision avoidance using Digital Elevation Model has been represented. An obstacle overfly in the vertical plane was shown.

Differential Geometry based Collision Avoidance Guidance for Multiple UAVs

A guidance law based on a differential geometry is proposed for UAV(Unmanned Aerial Vehicle) collision avoidance and formation reconfiguration. The proposed guidance law makes multiple UAVs avoid obstacles and provides a guideline for formation reconfigurtion. Differential geometry uses the line of sight vector and relative velocity vector information, and therefore it is effective to generate the real-time guidance command. Recognition process is introduced for obstacle recognition and judgement whether or not the collision avoidance is completed. Lyapunov theorem is used to prove the stability of the proposed guidance law. The analysis on the collision avoidance is also performed using the maximum angular rate of the UAV and the range of the recognition. Numerical simulation is performed to verify the performance of the proposed guidance and formation reconfiguration strategy.

Korean Wide Area Differential Global Positioning System Development Status and Preliminary Test Results

This paper is focused on dynamic modeling and control system design as well as vision based collision avoidance for multi-rotor unmanned aerial vehicles (UAVs). Multi-rotor UAVs are defined as rotary-winged UAVs with multiple rotors. These multi-rotor UAVs can be utilized in various military situations such as surveillance and reconnaissance. They can also be used for obtaining visual information from steep terrains or disaster sites. In this paper, a quad-rotor model is introduced as well as its control system, which is designed based on a proportional-integral-derivative controller and vision-based collision avoidance control system. Additionally, in order for a UAV to navigate safely in areas such as buildings and offices with a number of obstacles, there must be a collision avoidance algorithm installed in the UAV's hardware, which should include the detection of obstacles, avoidance maneuvering, etc. In this paper, the optical flow method, one of the vision-based collision avoidance techniques, is introduced, and multi-rotor UAV's collision avoidance simulations are described in various virtual environments in order to demonstrate its avoidance performance.

Optical Flow Based Collision Avoidance of Multi-Rotor UAVs in Urban Environments

This paper is focused on dynamic modeling and control system design as well as vision based collision avoidance for multi-rotor unmanned aerial vehicles (UAVs). Multi-rotor UAVs are defined as rotary-winged UAVs with multiple rotors. These multi-rotor UAVs can be utilized in various military situations such as surveillance and reconnaissance. They can also be used for obtaining visual information from steep terrains or disaster sites. In this paper, a quad-rotor model is introduced as well as its control system, which is designed based on a proportional-integral-derivative controller and vision-based collision avoidance control system. Additionally, in order for a UAV to navigate safely in areas such as buildings and offices with a number of obstacles, there must be a collision avoidance algorithm installed in the UAV’s hardware, which should include the detection of obstacles, avoidance maneuvering, etc. In this paper, the optical flow method, one of the vision-based collision avoidance techniques, is introduced, and multi-rotor UAV’s collision avoidance simulations are described in various virtual environments in order to demonstrate its avoidance performance.

Reactive Collision Avoidance of Using NonlinearGeometric and Differential Geometric Guidance

Reactive Collision Avoidance of Using NonlinearGeometric and Differential Geometric Guidance

Proportional navigation-based collision avoidance for UAVs

A collision avoidance algorithm for unmanned aerial vehicles (UAVs) based on the conventional proportional navigation (PN) guidance law is investigated. The proportional navigation guidance law being applied to a wide range of missile guidance problems is tailored to the collision avoidance of UAVs. This can be accomplished by guiding the relative velocity vector of the aircraft to a vector connecting the current aircraft position to the safety boundary of the target aircraft. Stability of the proposed algorithm is also studied using the circle criterion. The stability condition can be established by choosing the navigation coefficient within a certain bound. The guidance law is extended to 3-dimensional maneuver problems. Inherent simplicity and robustness of the PN guidance law provides satisfactory collision avoidance performance with different initial conditions.

UAV Optimal Cooperative Target Tracking and Collision Avoidance of Moving Objects

Effective target tracking and collision avoidance schemes are essential to the success of unmanned aerial vehicle (UAV) missions. In a dynamic environment, UAV path planning often relies on predicted obstacle and target motion. This paper presents an algorithm that predicts the trajectory of a moving object (target or obstacle) detected by a UAV. An extended Kalman filter is first employed to estimate the states of the object from its measured spatial position. The optimal object trajectory and its associated position prediction error are then calculated using the state equation defined for Kalman filtering. The proposed trajectory prediction scheme is afterward tested in a path planner which relies on decentralized cooperative predictive control to select optimal UAV trajectories as a function of the predicted target and obstacle trajectories. Simulation results are presented to demonstrate the effectiveness of the proposed approach.

Control of Formations of UAVs for Surveillance and Reconnaissance Missions

This paper presents a method for control of formations of Unmanned Aerial Vehicles (UAVs) in urban environments with several obstacles. Therefore the trajectories for each UAV are planned using mixed integer quadratic programming (MIQP) to describe a minimization problem. The result of this minimization problem then characterizes a collision free trajectory for each UAV using the commanded formations to fulfil the missions. The description of the UAVs, the inter UAV collision avoidance, the collision avoidance with obstacles as well as the description of formations will be shown in detail together with some simulation results in this paper. In addition the introduction explains the fields of interest in such formations of UAVs and what kind of advantage they can bring in comparison to today's solutions. The novelty in the approach in this paper is the description of formations of UAVs used in combination with MIQP to change formations, to add additional UAVs into an existing formation and to split formations, simply by changing some parameters in the description of the formation.