Cooperative Estimation of Moving Target Position Using Unmanned Aerial Vehicles

2017 ◽  
Author(s):  
Kamesh Subbarao ◽  
Pengkai Ru
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Target Position ◽  
Moving Target ◽  
Cooperative Estimation ◽  
Aerial Vehicles

Lyapunov vector-based formation tracking control for unmanned aerial vehicles with obstacle/collision avoidance

2019 ◽  
Vol 42 (5) ◽  
pp. 942-950
Author(s):  
Kai Chang ◽  
Dailiang Ma ◽  
Xingbin Han ◽  
Ning Liu ◽  
Pengpeng Zhao
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Potential Field ◽  
Formation Control ◽  
Control Method ◽  
Spherical Surface ◽  
Moving Target ◽  
Local Optima ◽  
Formation Tracking ◽  
Aerial Vehicles ◽  
Repulsive Forces

This paper presents a formation control method to solve the moving target tracking problem for a swarm of unmanned aerial vehicles (UAVs). The formation is achieved by the artificial potential field with both attractive and repulsive forces, and each UAV in the swarm will be driven into a leader-centered spherical surface. The leader is controlled by the attractive force by the moving target, while the Lyapunov vectors drive the leader UAV to a fly-around circle of the target. Furthermore, the rotational vector-based potential field is applied to achieve the obstacle avoidance of UAVs with smooth trajectories and avoid the local optima problem. The efficiency of the developed control scheme is verified by numerical simulations in four scenarios.

scholarly journals Accurate Landing of Unmanned Aerial Vehicles Using Ground Pattern Recognition

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1532 ◽  
Author(s):  
Jamie Wubben ◽  
Francisco Fabra ◽  
Carlos T. Calafate ◽  
Tomasz Krzeszowski ◽  
Johann M. Marquez-Barja ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Unmanned Aerial Vehicles ◽  
High Precision ◽  
Low Cost ◽  
Target Position ◽  
Flight Behavior ◽  
Ground Pattern ◽  
Aerial Vehicles ◽  
Exact Position ◽  
Precision Landing

Over the last few years, several researchers have been developing protocols and applications in order to autonomously land unmanned aerial vehicles (UAVs). However, most of the proposed protocols rely on expensive equipment or do not satisfy the high precision needs of some UAV applications such as package retrieval and delivery or the compact landing of UAV swarms. Therefore, in this work, a solution for high precision landing based on the use of ArUco markers is presented. In the proposed solution, a UAV equipped with a low-cost camera is able to detect ArUco markers sized 56 × 56 cm from an altitude of up to 30 m. Once the marker is detected, the UAV changes its flight behavior in order to land on the exact position where the marker is located. The proposal was evaluated and validated using both the ArduSim simulation platform and real UAV flights. The results show an average offset of only 11 cm from the target position, which vastly improves the landing accuracy compared to the traditional GPS-based landing, which typically deviates from the intended target by 1 to 3 m.

scholarly journals Motion-Encoded Electric Charged Particles Optimization for Moving Target Search Using Unmanned Aerial Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6568
Author(s):  
Mohammed A. Alanezi ◽  
Houssem R. E. H. Bouchekara ◽  
Mohammad S. Shahriar ◽  
Yusuf A. Sha’aban ◽  
Muhammad S. Javaid ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Unmanned Aerial Vehicles ◽  
Optimization Problem ◽  
Charged Particles ◽  
Moving Target ◽  
Moving Targets ◽  
Aerial Vehicles ◽  
Motion Paths ◽  
Moving Target Search ◽  
Different Characteristics

In this paper, a new optimization algorithm called motion-encoded electric charged particles optimization (ECPO-ME) is developed to find moving targets using unmanned aerial vehicles (UAV). The algorithm is based on the combination of the ECPO (i.e., the base algorithm) with the ME mechanism. This study is directly applicable to a real-world scenario, for instance the movement of a misplaced animal can be detected and subsequently its location can be transmitted to its caretaker. Using Bayesian theory, finding the location of a moving target is formulated as an optimization problem wherein the objective function is to maximize the probability of detecting the target. In the proposed ECPO-ME algorithm, the search trajectory is encoded as a series of UAV motion paths. These paths evolve in each iteration of the ECPO-ME algorithm. The performance of the algorithm is tested for six different scenarios with different characteristics. A statistical analysis is carried out to compare the results obtained from ECPO-ME with other well-known metaheuristics, widely used for benchmarking studies. The results found show that the ECPO-ME has great potential in finding moving targets, since it outperforms the base algorithm (i.e., ECPO) by as much as 2.16%, 5.26%, 7.17%, 14.72%, 0.79% and 3.38% for the investigated scenarios, respectively.

Continuous Monitoring of a Path-Constrained Moving Target by Multiple Unmanned Aerial Vehicles

2021 ◽  
pp. 1-10
Author(s):  
Camilla Tabasso ◽  
Calvin‘ Kielas-Jensen ◽  
Venanzio Cichella ◽  
Satyanarayana Manyam ◽  
David W. Casbeer ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Continuous Monitoring ◽  
Moving Target ◽  
Aerial Vehicles ◽  
Multiple Unmanned Aerial Vehicles

Unknown ground moving target tracking using multiple unmanned aerial vehicles

2017 ◽  
Vol 233 (3) ◽  
pp. 1021-1032 ◽  
Author(s):  
Shaoming He ◽  
Jiang Wang ◽  
Defu Lin
Keyword(s):  
Sliding Mode Control ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Sliding Mode ◽  
Moving Target ◽  
Guidance Law ◽  
Aerial Vehicles ◽  
Space Angle ◽  
Aerial Vehicle ◽  
Multiple Unmanned Aerial Vehicles

This paper investigates the problem of robust guidance law design for multiple unmanned aerial vehicles to achieve desired formation pattern for standoff tracking of an unknown ground moving target. The proposed guidance law consists of two main parts: relative range regulation and space angle control. For the first mission, a novel control law is proposed to regulate the relative distance between the unmanned aerial vehicle and the ground moving target to zero asymptotically based on adaptive sliding mode control approach. Considering the discontinuous property of the sign function, which is often used in traditional sliding mode control and will result in high-frequency chattering in the control channel, the proposed controller adopts the continuous saturation function for chattering elimination. Besides the continuous property, convergence to the origin asymptotically can be guaranteed theoretically with the proposed controller, which is quite different from traditional boundary layer technique, where only bounded motion around the sliding manifold can be ensured. For asymptotic stability, it is only required that the lumped uncertainty is bounded, but the upper bound may be unknown by virtue of the designed adaptive methodology. For space angle control, a new multiple leader–follower information architecture is introduced and an acceleration command is then derived for each unmanned aerial vehicle to space them about the loiter circle defined by the first controller. Simulation results with different conditions clearly demonstrate the superiority of the proposed formulation.

Sign in / Sign up

Export Citation Format

Share Document