Multi-UAV cooperative target encirclement within an annular virtual tube

Gao, Yan; Bai, Chenggang; Zhang, Lei; Quan, Quan

doi:10.1016/j.ast.2022.107800

Cited by 16 publications

(10 citation statements)

References 29 publications

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“…In our previous work, the waypoints are used to obtain the path, and the gates' information help establish the virtual tube [20]. The process of establishing the virtual tube includes two parts: the generator curve and the cross section [21]. Intuitively, a virtual tube is generated by a cross section perpendicularly moving along the generator curve, and the surface is the boundary of the virtual tube [22].…”

Section: A Virtual Tube Modeling Based On Gatesmentioning

confidence: 99%

Autonomous Drone Racing: Time-Optimal Spatial Iterative Learning Control within a Virtual Tube

Gao

Che

et al. 2023

2023 IEEE International Conference on Robotics and Automation (ICRA)

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It is often necessary for drones to complete delivery, photography, and rescue in the shortest time to increase efficiency. Many autonomous drone races provide platforms to pursue algorithms to finish races as quickly as possible for the above purpose. Unfortunately, existing methods often fail to keep training and racing time short in drone racing competitions. This motivates us to develop a high-efficient learning method by imitating the training experience of top racing drivers. Unlike traditional iterative learning control methods for accurate tracking, the proposed approach iteratively learns a trajectory online to finish the race as quickly as possible. Simulations and experiments using different models show that the proposed approach is model-free and is able to achieve the optimal result with low computation requirements. Furthermore, this approach surpasses some state-of-the-art methods in racing time on a benchmark drone racing platform. An experiment on a real quadcopter is also performed to demonstrate its effectiveness.

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Section: A Virtual Tube Modeling Based On Gatesmentioning

confidence: 99%

Autonomous Drone Racing: Time-Optimal Spatial Iterative Learning Control within a Virtual Tube

Gao

Che

et al. 2023

2023 IEEE International Conference on Robotics and Automation (ICRA)

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“…Other objectives can be considered according to the specific applications. There are many kinds of virtual tubes in the literature, such as straight-line virtual tube [10], trapezoid virtual tube [11], [12], connected quadrangle virtual tube [11], annular virtual tube [13], curve virtual tube [14], [15]. Besides, some similar concepts have been proposed in the literature, such as the lane for autonomous road vehicles in [16], [17] and the safe flight corridor for the multicopter in [18].…”

Section: B Algorithms For Passing-through Controlmentioning

confidence: 99%

Distributed Control for a Multiagent System to Pass Through a Connected Quadrangle Virtual Tube

Gao

Bai

Quan

2023

IEEE Trans. Control Netw. Syst.

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This survey presents a comprehensive review of various methods and algorithms related to passing-through control of multi-robot systems in cluttered environments. Numerous studies have investigated this area, and we identify several avenues for enhancing existing methods. This survey describes some models of robots and commonly considered control objectives, followed by an in-depth analysis of four types of algorithms that can be employed for passing-through control: leader-follower formation control, multi-robot trajectory planning, control-based methods, and virtual tube planning and control. Furthermore, we conduct a comparative analysis of these techniques and provide some subjective and general evaluations.

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“…The virtual tube ensures the safety of robots and cities. Then, to guide the swarm to pass through corridors, doors and windows, and surround surveillance targets without diverging (Gao et al (2022)), we have also generalized the definition of virtual tubes and proposed the curved virtual tube (Quan et al (2023b)). This concept of the curve virtual tube is similar to the lane for autonomous road vehicles in Rasekhipour et al (2016), Luo et al (2018) and corridor for a multi-UAV system in Nagrare et al (2022).…”

Section: Introductionmentioning

confidence: 99%

Optimal virtual tube planning and control for swarm robotics

Mao,

Fu,

Quan

2023

The International Journal of Robotics Research

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This paper presents a novel method for efficiently solving a trajectory planning problem for swarm robotics in cluttered environments. Recent research has demonstrated high success rates in real-time local trajectory planning for swarm robotics in cluttered environments, but optimizing trajectories for each robot is still computationally expensive, with a computational complexity from [Formula: see text] to [Formula: see text] where [Formula: see text] is the number of parameters in the parameterized trajectory, [Formula: see text] is precision, and [Formula: see text] is the number of iterations with respect to [Formula: see text] and [Formula: see text]. Furthermore, the swarm is difficult to move as a group. To address this issue, we define and then construct the optimal virtual tube, which includes infinite optimal trajectories. Under certain conditions, any optimal trajectory in the optimal virtual tube can be expressed as a convex combination of a finite number of optimal trajectories, with a computational complexity of [Formula: see text]. Afterward, a hierarchical approach including a planning method of the optimal virtual tube with minimizing energy and distributed model predictive control is proposed. In simulations and experiments, the proposed approach is validated and its effectiveness over other methods is demonstrated through comparison.

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Multi-UAV cooperative target encirclement within an annular virtual tube

Cited by 16 publications

References 29 publications

Autonomous Drone Racing: Time-Optimal Spatial Iterative Learning Control within a Virtual Tube

Autonomous Drone Racing: Time-Optimal Spatial Iterative Learning Control within a Virtual Tube

Distributed Control for a Multiagent System to Pass Through a Connected Quadrangle Virtual Tube

Optimal virtual tube planning and control for swarm robotics

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