A cooperative line-of-sight guidance law for a three-dimensional phantom track generation using unmanned aerial vehicles

2012 ◽  
Vol 227 (6) ◽  
pp. 897-915 ◽  
Author(s):  
Il-Hyoung Lee ◽  
Hyochoong Bang
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Three Dimensional ◽  
Line Of Sight ◽  
Guidance Law ◽  
Aerial Vehicles

Three-dimensional multiple unmanned aerial vehicles formation control strategy based on second-order consensus

2016 ◽  
Vol 232 (3) ◽  
pp. 481-491 ◽  
Author(s):  
Xu Zhu ◽  
Xun-Xun Zhang ◽  
Mao-De Yan ◽  
Yao-Hong Qu ◽  
Hai Lin
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Cooperative Control ◽  
Formation Control ◽  
Three Dimensional ◽  
Second Order ◽  
Guidance Law ◽  
Aerial Vehicles ◽  
Cooperative Guidance ◽  
Consensus Strategy ◽  
Multiple Unmanned Aerial Vehicles

Considering three-dimensional formation control for multiple unmanned aerial vehicles, this paper proposes a second-order consensus strategy by utilizing the position and velocity coordinate variables. To maintain the specified geometric configuration, a cooperative guidance algorithm and a cooperative control algorithm are proposed together to manage the position and attitude, respectively. The cooperative guidance law, which is designed as a second-order consensus algorithm, provides the desired pitch rate, heading rate and acceleration. In addition, a synchronization technology is put forward to reduce the influence of the measurement errors for the cooperative guidance law. The cooperative control law, regarding the output of the cooperative guidance law as its input, is designed by deducing the state-space expression of both the longitudinal and lateral motions. The formation stability is analyzed to give a sufficient and necessary condition. Finally, the simulations for the three-dimensional formation control demonstrate the feasibility and effectiveness of the second-order consensus strategy.

Dynamic Inversion-Based Nonlinear Aiming Point Guidance of Unmanned Aerial Vehicles for Reactive Obstacle Avoidance

2013 ◽  
Vol 01 (02) ◽  
pp. 259-275 ◽  
Author(s):  
Ramsingh G. Raja ◽  
Charu Chawla ◽  
Radhakant Padhi
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Velocity Vector ◽  
Three Dimensional ◽  
Dynamic Inversion ◽  
Mass Model ◽  
Guidance Law ◽  
Aerial Vehicles ◽  
Angular Correction ◽  
Aerial Vehicle ◽  
Reactive Collision

A dynamic inversion-based three-dimensional nonlinear aiming point guidance law is presented in this paper for reactive collision avoidance of unmanned aerial vehicles. When an obstacle is detected in the close vicinity and collision is predicted, an artificial safety sphere is put around the center of the obstacle. Next, the velocity vector of the vehicle is realigned towards an 'aiming point' on the surface of the sphere in such a way that passing through it can guarantee safe avoidance of the obstacle. The guidance command generation is based on angular correction between the actual and the desired direction of the velocity vector. Note that the velocity vector gets aligned along the selected aiming point quickly (i.e., within a fraction of the available time-to-go), which makes it possible to avoid pop-up obstacles. The guidance algorithm has been verified with simulations carried out both for single obstacles as well as for multiple obstacles on the path and also with different safety sphere sizes around the obstacles. The proposed algorithm has been validated using both kinematic as well as point mass model of a prototype unmanned aerial vehicle. For better confidence, results have also been validated by incorporating a first-order autopilot models for the velocity vector magnitude and directions.

Fully distributed guidance laws for unmanned aerial vehicles formation flight

2019 ◽  
Vol 42 (5) ◽  
pp. 965-980 ◽  
Author(s):  
Xiaoqian Wei ◽  
Jianying Yang ◽  
Xiangru Fan
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Group Formation ◽  
Formation Flight ◽  
Line Of Sight ◽  
Time Varying ◽  
Flight Trajectory ◽  
Adaptive Technology ◽  
Guidance Law ◽  
Aerial Vehicles ◽  
Guidance Laws

In this paper, three fully distributed guidance laws are designed for unmanned aerial vehicles formation flight, which have the following advantages. Adaptive technology in novel guidance laws can adapt to various graphs that only need one spanning tree. Cooperative formation does not need to set the virtual structure of formation in advance, but only needs to adjust the formation parameters in the guidance law to achieve the desired time-varying formation. This paper uses a guidance law perpendicular to the line of sight to make the flight trajectory more straight; hence, enhancing its applicability in real-world scenarios. These new guidance laws also enable group formation transformation and can optimize the unmanned aerial vehicles’ formation without global information to obtain the optimum performance of the formation. The simulation results show the practicability and effectiveness of the new method.

A method for autonomous collision-free navigation of a quadrotor UAV in unknown tunnel-like environments

Robotica ◽  
2021 ◽  
pp. 1-27
Author(s):  
Taha Elmokadem ◽  
Andrey V. Savkin
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Autonomous Underwater Vehicles ◽  
Three Dimensional ◽  
Underwater Vehicles ◽  
Practical Implementation ◽  
Challenging Problem ◽  
Quadrotor Uav ◽  
Navigation Algorithm ◽  
Aerial Vehicles ◽  
Quadrotor Uavs

Abstract Unmanned aerial vehicles (UAVs) have become essential tools for exploring, mapping and inspection of unknown three-dimensional (3D) tunnel-like environments which is a very challenging problem. A computationally light navigation algorithm is developed in this paper for quadrotor UAVs to autonomously guide the vehicle through such environments. It uses sensors observations to safely guide the UAV along the tunnel axis while avoiding collisions with its walls. The approach is evaluated using several computer simulations with realistic sensing models and practical implementation with a quadrotor UAV. The proposed method is also applicable to other UAV types and autonomous underwater vehicles.

3D Nonlinear Guidance Law for Bank-to-Turn Missile

2011 ◽  
Vol 317-319 ◽  
pp. 727-733
Author(s):  
Shuang Chun Peng ◽  
Liang Pan ◽  
Tian Jiang Hu ◽  
Lin Cheng Shen
Keyword(s):  
Three Dimensional ◽  
Lyapunov Theory ◽  
Line Of Sight ◽  
Rate Model ◽  
Guidance Law ◽  
Terminal Constraints ◽  
Guidance Laws ◽  
3D Guidance ◽  
Guidance Model ◽  
Vector Description

A new three-dimensional (3D) nonlinear guidance law is proposed and developed for bank-to-turn (BTT) with motion coupling. First of all, the 3D guidance model is established. In detail, the line-of-sight (LOS) rate model is established with the vector description method, and the kinematics model is divided into three terms of pitching, swerving and coupling, then by using the twist-based method, the LOS direction changing model is built for designing the guidance law with terminal angular constraints. Secondly, the 3D guidance laws are designed with Lyapunov theory, corresponding to no terminal constraints and terminal constraints, respectively. And finally, the simulation results show that the proposed guidance law can effectively satisfy the guidance precision requirements of BTT missile.

scholarly journals Vision-Based Target Three-Dimensional Geolocation Using Unmanned Aerial Vehicles

2018 ◽  
Vol 65 (10) ◽  
pp. 8052-8061 ◽  
Author(s):  
Lele Zhang ◽  
Fang Deng ◽  
Jie Chen ◽  
Yingcai Bi ◽  
Swee King Phang ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Three Dimensional ◽  
Aerial Vehicles

A survey on stereo vision-based autonomous navigation for multi-rotor MUAVs

Robotica ◽  
2018 ◽  
Vol 36 (8) ◽  
pp. 1225-1243 ◽  
Author(s):  
Jose-Pablo Sanchez-Rodriguez ◽  
Alejandro Aceves-Lopez
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Stereo Vision ◽  
Autonomous Navigation ◽  
Three Dimensional ◽  
Field Of View ◽  
Line Of Sight ◽  
Onboard Computer ◽  
Low Weight ◽  
Vision Based Navigation ◽  
Difficult Challenge

SUMMARYThis paper presents an overview of the most recent vision-based multi-rotor micro unmanned aerial vehicles (MUAVs) intended for autonomous navigation using a stereoscopic camera. Drone operation is difficult because pilots need the expertise to fly the drones. Pilots have a limited field of view, and unfortunate situations, such as loss of line of sight or collision with objects such as wires and branches, can happen. Autonomous navigation is an even more difficult challenge than remote control navigation because the drones must make decisions on their own in real time and simultaneously build maps of their surroundings if none is available. Moreover, MUAVs are limited in terms of useful payload capability and energy consumption. Therefore, a drone must be equipped with small sensors, and it must carry low weight. In addition, a drone requires a sufficiently powerful onboard computer so that it can understand its surroundings and navigate accordingly to achieve its goal safely. A stereoscopic camera is considered a suitable sensor because of its three-dimensional (3D) capabilities. Hence, a drone can perform vision-based navigation through object recognition and self-localise inside a map if one is available; otherwise, its autonomous navigation creates a simultaneous localisation and mapping problem.

Optimized artificial potential field algorithm to multi-unmanned aerial vehicle coordinated trajectory planning and collision avoidance in three-dimensional environment

2019 ◽  
Vol 233 (16) ◽  
pp. 6032-6043 ◽  
Author(s):  
Jun Tang ◽  
Jiayi Sun ◽  
Cong Lu ◽  
Songyang Lao
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Unmanned Aerial Vehicle ◽  
Trajectory Planning ◽  
Potential Field ◽  
Three Dimensional ◽  
Artificial Potential Field ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Vehicle Trajectory

Multi-unmanned aerial vehicle trajectory planning is one of the most complex global optimum problems in multi-unmanned aerial vehicle coordinated control. Results of recent research works on trajectory planning reveal persisting theoretical and practical problems. To mitigate them, this paper proposes a novel optimized artificial potential field algorithm for multi-unmanned aerial vehicle operations in a three-dimensional dynamic space. For all purposes, this study considers the unmanned aerial vehicles and obstacles as spheres and cylinders with negative electricity, respectively, while the targets are considered spheres with positive electricity. However, the conventional artificial potential field algorithm is restricted to a single unmanned aerial vehicle trajectory planning in two-dimensional space and usually fails to ensure collision avoidance. To deal with this challenge, we propose a method with a distance factor and jump strategy to resolve common problems such as unreachable targets and ensure that the unmanned aerial vehicle does not collide into the obstacles. The method takes companion unmanned aerial vehicles as the dynamic obstacles to realize collaborative trajectory planning. Besides, the method solves jitter problems using the dynamic step adjustment method and climb strategy. It is validated in quantitative test simulation models and reasonable results are generated for a three-dimensional simulated urban environment.

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