scholarly journals UAV Mission Planning Resistant to Weather Uncertainty

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 515 ◽  
Author(s):  
Amila Thibbotuwawa ◽  
Grzegorz Bocewicz ◽  
Grzegorz Radzki ◽  
Peter Nielsen ◽  
Zbigniew Banaszak
Keyword(s):  
Wind Speed ◽  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Weather Conditions ◽  
Mission Planning ◽  
Alternative Strategies ◽  
Fleet Size ◽  
Aerial Vehicles ◽  
Time Period ◽  
Weather Uncertainty

Fleet mission planning for Unmanned Aerial Vehicles (UAVs) is the process of creating flight plans for a specific set of objectives and typically over a time period. Due to the increasing focus on the usage of large UAVs, a key challenge is to conduct mission planning addressing changing weather conditions, collision avoidance, and energy constraints specific to these types of UAVs. This paper presents a declarative approach for solving the complex mission planning resistant to weather uncertainty. The approach has been tested on several examples, analyzing how customer satisfaction is influenced by different values of the mission parameters, such as the fleet size, travel distance, wind direction, and wind speed. Computational experiments show the results that allow assessing alternative strategies of UAV mission planning.

scholarly journals Modelling Robust Delivery Scenarios for a Fleet of Unmanned Aerial Vehicles in Disaster Relief Missions

2021 ◽  
Vol 103 (4) ◽  
Author(s):  
G. Radzki ◽  
P. Golinska-Dawson ◽  
G. Bocewicz ◽  
Z. Banaszak
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Disaster Relief ◽  
Weather Conditions ◽  
Fleet Size ◽  
Weather Forecasts ◽  
Disaster Relief Operations ◽  
Aerial Vehicles ◽  
Study Results ◽  
Battery Capacity ◽  
Relief Operations

AbstractBesides commercial and military applications, unmanned aerial vehicles (UAVs) are now used more commonly in disaster relief operations. This study proposes a novel model for proactive and reactive planning (different scenarios) that allow for a higher degree of realism, thus a higher likelihood for a mission of being executed according to the plan even when weather forecasts are changing. The novelty of this study results from the addition of a function of resistance of UAVs mission to changes in weather conditions. We link the influence of weather conditions on the UAV’s energy consumption. The goal is to ensure the completion of planned deliveries by a fleet of UAVs under changing weather conditions before their batteries discharge and to identify the emergency route for returned if the mission cannot be completed. An approach based on constraint programming is proposed, as it has proven to be effective in various contexts, especially related to the nonlinearity of the system’s characteristics. The proposed approach has been tested on several instances, which have allowed for analyzing how the plan of mission is robust to the changing weather conditions with different parameters, such as the fleet size, battery capacity, and distribution network layout.

Intelligent cooperative collision avoidance via fuzzy potential fields

Robotica ◽  
2021 ◽  
pp. 1-20
Author(s):  
Daegyun Choi ◽  
Anirudh Chhabra ◽  
Donghoon Kim
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Fuzzy Inference ◽  
Potential Fields ◽  
Rule Base ◽  
Local Minima ◽  
Inference System ◽  
Aerial Vehicles ◽  
Different Shapes ◽  
Simulation Results

Summary This paper proposes an intelligent cooperative collision avoidance approach combining the enhanced potential field (EPF) with a fuzzy inference system (FIS) to resolve local minima and goal non-reachable with obstacles nearby issues and provide a near-optimal collision-free trajectory. A genetic algorithm is utilized to optimize parameters of membership function and rule base of the FISs. This work uses a single scenario containing all issues and interactions among unmanned aerial vehicles (UAVs) for training. For validating the performance, two scenarios containing obstacles with different shapes and several UAVs in small airspace are considered. Multiple simulation results show that the proposed approach outperforms the conventional EPF approach statistically.

scholarly journals Distributed Cooperative Avoidance Control for Multi-Unmanned Aerial Vehicles

Actuators ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 1 ◽  
Author(s):  
Sunan Huang ◽  
Rodney Swee Huat Teo ◽  
Wenqi Liu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Case Studies ◽  
Collision Avoidance ◽  
Hardware In The Loop ◽  
Crucial Issue ◽  
Communication Failure ◽  
Aerial Vehicles ◽  
Avoidance Control ◽  
Velocity Obstacle ◽  
Multi Uav

It is well-known that collision-free control is a crucial issue in the path planning of unmanned aerial vehicles (UAVs). In this paper, we explore the collision avoidance scheme in a multi-UAV system. The research is based on the concept of multi-UAV cooperation combined with information fusion. Utilizing the fused information, the velocity obstacle method is adopted to design a decentralized collision avoidance algorithm. Four case studies are presented for the demonstration of the effectiveness of the proposed method. The first two case studies are to verify if UAVs can avoid a static circular or polygonal shape obstacle. The third case is to verify if a UAV can handle a temporary communication failure. The fourth case is to verify if UAVs can avoid other moving UAVs and static obstacles. Finally, hardware-in-the-loop test is given to further illustrate the effectiveness of the proposed method.

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.

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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