scholarly journals Formation flight and collision avoidance for multiple UAVs based on modified tentacle algorithm in unstructured environments

PLoS ONE ◽  
2017 ◽  
Vol 12 (8) ◽  
pp. e0182006 ◽  
Author(s):  
Minghuan Zhang
Keyword(s):  
Collision Avoidance ◽  
Formation Flight ◽  
Unstructured Environments ◽  
Multiple Uavs

scholarly journals Incorporation of Potential Fields and Motion Primitives for the Collision Avoidance of Unmanned Aircraft

2021 ◽  
Vol 11 (7) ◽  
pp. 3103
Author(s):  
Kyuman Lee ◽  
Daegyun Choi ◽  
Donghoon Kim
Keyword(s):  
Collision Avoidance ◽  
Search Algorithm ◽  
Unmanned Aircraft ◽  
Artificial Potential Field ◽  
Tree Search ◽  
Local Minima ◽  
Collision Risk ◽  
Motion Primitives ◽  
Multiple Uavs ◽  
Tree Search Algorithm

Collision avoidance (CA) using the artificial potential field (APF) usually faces several known issues such as local minima and dynamically infeasible problems, so unmanned aerial vehicles’ (UAVs) paths planned based on the APF are safe only in a certain environment. This research proposes a CA approach that combines the APF and motion primitives (MPs) to tackle the known problems associated with the APF. Since MPs solve for a locally optimal trajectory with respect to allocated time, the trajectory obtained by the MPs is verified as dynamically feasible. When a collision checker based on the k-d tree search algorithm detects collision risk on extracted sample points from the planned trajectory, generating re-planned path candidates to avoid obstacles is performed. After rejecting unsafe route candidates, one applies the APF to select the best route among the remaining safe-path candidates. To validate the proposed approach, we simulated two meaningful scenario cases—the presence of static obstacles situation with local minima and dynamic environments with multiple UAVs present. The simulation results show that the proposed approach provides smooth, efficient, and dynamically feasible pathing compared to the APF.

scholarly journals Decentralized 3D Collision Avoidance for Multiple UAVs in Outdoor Environments

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4101 ◽  
Author(s):  
Eduardo Ferrera ◽  
Alfonso Alcántara ◽  
Jesús Capitán ◽  
Angel Castaño ◽  
Pedro Marrón ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
System Integration ◽  
Field Experiments ◽  
Positioning Systems ◽  
Wind Gusts ◽  
Aerial Vehicles ◽  
Multiple Uavs ◽  
Outdoor Environments ◽  
External Conditions ◽  
Field Experimentation

The use of multiple aerial vehicles for autonomous missions is turning into commonplace. In many of these applications, the Unmanned Aerial Vehicles (UAVs) have to cooperate and navigate in a shared airspace, becoming 3D collision avoidance a relevant issue. Outdoor scenarios impose additional challenges: (i) accurate positioning systems are costly; (ii) communication can be unreliable or delayed; and (iii) external conditions like wind gusts affect UAVs’ maneuverability. In this paper, we present 3D-SWAP, a decentralized algorithm for 3D collision avoidance with multiple UAVs. 3D-SWAP operates reactively without high computational requirements and allows UAVs to integrate measurements from their local sensors with positions of other teammates within communication range. We tested 3D-SWAP with our team of custom-designed UAVs. First, we used a Software-In-The-Loop simulator for system integration and evaluation. Second, we run field experiments with up to three UAVs in an outdoor scenario with uncontrolled conditions (i.e., noisy positioning systems, wind gusts, etc). We report our results and our procedures for this field experimentation.

Multivariable adaptive distributed leader-follower flight control for multiple UAVs formation

2017 ◽  
Vol 121 (1241) ◽  
pp. 877-900 ◽  
Author(s):  
Y. Xu ◽  
Z. Zhen
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Flight Control ◽  
Control Strategy ◽  
Formation Control ◽  
Parametric Uncertainty ◽  
Lyapunov Theory ◽  
Formation Flight ◽  
Flight Control System ◽  
Multiple Uavs

ABSTRACTThe Unmanned Aerial Vehicles (UAVs) become more and more popular due to various potential application fields. This paper studies the distributed leader-follower formation flight control problem of multiple UAVs with uncertain parameters for both the leader and followers. This problem has not been addressed in the literature. Most of the existing literature considers the leader-follower formation control strategy with parametric uncertainty for the followers. However, they do not take the leader parametric uncertainty into account. Meanwhile, the distributed control strategy depends on less information interactions and is more likely to avoid information conflict. The dynamic model of the UAVs is established based on the aerodynamic parameters. The establishment of the topology structure between a collection of UAVs is based on the algebraic graph theory. To handle the parametric uncertainty of the UAVs dynamics, a multivariable model reference adaptive control (MRAC) method is addressed to design the control law, which enables follower UAVs to track the leader UAV. The stability of the formation flight control system is proved by the Lyapunov theory. Simulation results show that the proposed distributed adaptive leader-following formation flight control system has stronger robustness and adaptivity than the fixed control system, as well as the existing adaptive control system.

scholarly journals Collision Avoidance in Fixed-Wing UAV Formation Flight Based on a Consensus Control Algorithm

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 43672-43682 ◽  
Author(s):  
Jialong Zhang ◽  
Jianguo Yan ◽  
Pu Zhang ◽  
Xiangjie Kong
Keyword(s):  
Collision Avoidance ◽  
Control Algorithm ◽  
Formation Flight ◽  
Consensus Control

Design and flight-stability analysis of a closed fixed-wing unmanned aerial vehicle formation controller

2018 ◽  
Vol 233 (8) ◽  
pp. 1045-1054 ◽  
Author(s):  
Jialong Zhang ◽  
Bing Xiao ◽  
Maolong Lv ◽  
Qiang Zhang
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
High Speed ◽  
Physical Simulation ◽  
Controller Design ◽  
Formation Flight ◽  
External Factors ◽  
Flight Stability ◽  
Aerial Vehicles ◽  
Closed Formation

This article addresses a flight-stability problem for the multiple unmanned aerial vehicles cooperative formation flight in the process of the closed and high-speed flight. The main objective is to design a cooperative formation controller with known external factors, and this controller can keep the consensus of attitude and position and reduce the communication delay between any two unmanned aerial vehicles and increase unmanned aerial vehicles formation cruise time under the known external factors. Known external factors are taken into consideration, and longitude maneuvers using nonlinear thrust vectors were employed with unsteady aerodynamic models, according to the attitude and position of unmanned aerial vehicles, which were employed as corresponding input signals for studying the dynamic characteristics of unmanned aerial vehicles formation flight. In addition, the relative distance between any two unmanned aerial vehicles was not allowed to exceed their safe distance so that the controller could perform collision avoidance. An analysis of formation flight distance error shows that it converged to a fixed value that well ensured unmanned aerial vehicles formation flight stability. The experimental results show that the controller can improve the speed of a closed formation effectively and maintain the stability of formation flight, which provides a method for closed formation flight controller design and collision avoidance for any two unmanned aerial vehicles. Meanwhile, the effectiveness of proposed controller is fully proved by semi-physical simulation platform.

2A1-W05 Guidance Control with Collision Avoidance for Multiple UAVs under Communication Restricted(Cooperation Control of Multi Robots)

2014 ◽  
Vol 2014 (0) ◽  
pp. _2A1-W05_1-_2A1-W05_4
Author(s):  
Yoshihiko AIDA ◽  
Yohei FUJISAWA ◽  
Satoshi SUZUKI ◽  
Kojiro IIZUKA ◽  
Takashi KAWAMURA ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Guidance Control ◽  
Multiple Uavs ◽  
Restricted Cooperation
Sign in / Sign up

Export Citation Format

Share Document