A Time Optimal Reactive Collision Avoidance Method for UAVs Based on a Modified Collision Cone Approach

Gnanasekera, Manaram; Katupitiya, Jayantha

doi:10.1109/iros45743.2020.9341259

Cited by 5 publications

(5 citation statements)

References 16 publications

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“…In general, the purpose of the UAV swarm is to travel to a target by avoiding some disjoint obstacles. Inspired by the collision cone approach (Gnanasekera and Katupitiya, 2020), an obstacles avoidance rule is generated to adjust the velocity direction of each UAV to avoid obstacles. As shown in Figure 5, the obstacle avoidance can be realized by adjusting the velocity direction outside the collision cone.…”

Section: Distributed Uav Swarm Control Methodsmentioning

confidence: 99%

“…In this paper, to realize the simultaneous consideration of external security and swarm internal security, an obstacle avoidance approach and the limited swarm interaction are considered. To adapt to a more complex flight environment, the collision cone approach (Gnanasekera and Katupitiya, 2020; Manathara and Ghose, 2011) is used to generate the obstacle avoidance control component. As there are blind areas in most biological vision in nature, the limited view angle is introduced into the neighbor selection method to generate the distributed UAV swarm control framework.…”

Section: Introductionmentioning

confidence: 99%

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Distributed UAV swarm control framework with limited interaction for obstacle avoidance

Zhu

Deng

2022

AEAT

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Purpose The purpose of this paper is to propose a distributed unmanned aerial vehicle (UAV) swarm control method to ensure safety and obstacle avoidance during swarm flight and realize effective guidance. Design/methodology/approach This paper proposes a distributed UAV swarm control framework with limited interaction. UAVs in the swarm realize the selection of limited interactive neighbors according to the random line of sight and limited field of view. The designed interaction force and obstacle avoidance mechanism are combined to ensure the safety of UAVs and avoid collisions and obstacles. Informed UAVs are deployed to guide the swarm to move in the desired direction. Findings The proposed distributed swarm control framework achieves high safety of swarm motion and the participation of informed UAVs is conducive to the guidance of the UAV swarm. Simulation results demonstrate the feasibility and effectiveness of the proposed approach. Practical implications The UAV swarm control method developed in this paper can be applied to the practice of UAV swarm control. Originality/value A distributed UAV swarm control method is proposed to ensure the effective control of the consistency and safety of swarm motion.

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Section: Distributed Uav Swarm Control Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed UAV swarm control framework with limited interaction for obstacle avoidance

Zhu

Deng

2022

AEAT

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“…The obstacle avoidance direction of the UAV follows the VO method avoidance mechanism (the relative velocity direction deviates from the obstacle), as shown in Figures 7 and 8. The relative velocity solution is expressed by Equation (21).…”

Section: Obstacle Avoidancementioning

confidence: 99%

“…For high‐speed and nonlinearly moving obstacles, the relative velocity direction may point to the obstacle when a collision is about to occur, which is not conducive to smooth obstacle avoidance by UAV. In Reference 21, a collision evaluation model based on the collision cone method and the prediction of the collision time was established to judge an imminent collision. A dynamic obstacle avoidance method that considers the aerodynamics of a UAV was proposed in Reference 22, in which the VO was combined with a cubic uniform B‐spline curve to generate a smooth obstacle avoidance path.…”

Section: Introductionmentioning

confidence: 99%

Dynamic smooth and stable obstacle avoidance for unmanned aerial vehicle based on collision prediction

Ma,

Cai,

et al. 2023

Optim Control Appl Methods

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Autonomous dynamic obstacle avoidance of unmanned aerial vehicles (UAVs) based on collision prediction is critical for stable flight missions. UAVs must deal with high‐speed and nonlinearly moving obstacles that obey nonlinear dynamics, which are one of the numerous objects affecting stable flight. To satisfy the requirements of smooth flight and attitude stability, a novel dynamic smooth obstacle avoidance (QVA) method based on obstacle trajectory prediction is proposed. To predict the dynamic obstacle trajectories, a trajectory prediction (QLTP) method using a quasi‐linear parameter varying representations is proposed. The proposed QVA integrates the QLTP approach, velocity obstacle (VO) approach, and artificial potential field (APF) methods. The QVA detects an imminent collision based on the QLTP method, and then replans the UAV path based on the VO method at the time of the predicted collision. The UAV tracks planned waypoints for collision avoidance. To ensure the flight safety of the UAV, a virtual APF is constructed with waypoints as local targets and obstacles. The simulation results show that the proposed method performs better than the improved APF and VO methods in terms of the smoothness of the obstacle avoidance path and the stability of the UAV attitude.

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“…Model-based methods are designed based on accurate models, such as geometric model, artificial potential field method, velocity obstacle (VO) method and so on. However, due to the limitations of realistic environments and the constraints of UAV itself, many of the existing methods have a large amount of calculation and are not suitable for reactive collision avoidance of multi-vehicle systems [11]. Fortunately, VO method has the ability to predict the collision in advance, and the calculation requirements are not high, and it is more suitable for multi-obstacle avoidance in complex environments [12].…”

Section: Introductionmentioning

confidence: 99%

Cooperative Obstacle Avoidance for Multiple UAVs Using Spline_VO Method

Peng

Meng

2022

Sensors

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In order to solve multiple unmanned aerial vehicle (UAV) dynamic collision avoidance, a cooperative obstacle avoidance algorithm considering UAV’s kinematic constraints has been developed. In the proposed algorithm, the useful information of UAVs is screened out by a Heartbeat information filtering mechanism and fused by the user datagram protocol (UDP) communication method, which improves communication performance among UAVs. In addition, the velocity obstacle (VO) method combined with cubic uniform B-spline curve is used to avoid obstacles and generate smooth paths, which can be applied to practical scenes. Finally, dynamic and static obstacle avoidance simulations are carried out to verify the effectiveness of the proposed algorithm.

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A Time Optimal Reactive Collision Avoidance Method for UAVs Based on a Modified Collision Cone Approach

Cited by 5 publications

References 16 publications

Distributed UAV swarm control framework with limited interaction for obstacle avoidance

Distributed UAV swarm control framework with limited interaction for obstacle avoidance

Dynamic smooth and stable obstacle avoidance for unmanned aerial vehicle based on collision prediction

Cooperative Obstacle Avoidance for Multiple UAVs Using Spline_VO Method

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