Distributed control for a robotic swarm to pass through a curve virtual tube

Quan, Quan; Gao, Yan; Bai, Chenggang

doi:10.1016/j.robot.2023.104368

Cited by 9 publications

(26 citation statements)

References 37 publications

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“…Besides, it is required that r d > r c > r s + r a . In our previous work, 14 the constant r a is called avoidance radius. The detailed properties of V m,ij and V t,i are also presented in Reference 14.…”

Section: Distributed Controller For Passing Through the Curve Virtual...mentioning

confidence: 99%

“…Theorem 1. 14 Under Assumptions 2-5, suppose that (i) all robots have a single-integrator model ṗi = v c,i , i = 1, … , M; (ii) the velocity command for the ith robot is designed as (23); (iii)   is wide enough for at least one robot to pass through. Then, we have t 1 > 0 such that all robots can pass through   at t ≥ t 1 , meanwhile, guaranteeing…”

Section: Assumption 4 the Robots' Initial Conditions Satisfymentioning

confidence: 99%

“…The reason is that u 5,i can be equivalent to the derivative of a limited potential function, which is easy to add to the final Lyapunov-like function. 14 Then, according to Theorem 1 and Lemma 1, we have t 1 > 0 such that all robots can pass through…”

Section: Analysis: Control Effectiveness Of Robust Swarm Controllermentioning

confidence: 99%

“…As long as v m > ‖ ‖ ṗd ‖ ‖ , this saturation process has no negative effect on the system safety and stability. 14 Four simulations are carried out with k c = 0, 1, 5, 10. Other parameters are set as k t = 5, r s = 1m, r a = 3m, 𝜖 m = 10 −6 , 𝜖 s = 10 −6 , and v m = 2m/s.…”

Section: Simulations To Show Effectiveness Of Robot Cohesion Term In ...mentioning

confidence: 99%

“…in which a c,i ∈ R 2 indicates the acceleration command of the ith robot, and p i , v i ∈ R 2 stand for the position and velocity of the ith robot, respectively. The controller proposed in our previous work 14 is a type of vector field controller. Hence, a hierarchical control architecture is necessary.…”

Section: Robot Kinematics Modelmentioning

confidence: 99%

See 4 more Smart Citations

Robust distributed control within a curve virtual tube for a robotic swarm under self‐localization drift and precise relative navigation

Gao

Bai

Quan

2023

Intl J Robust & Nonlinear

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To guide the movement of a robotic swarm in a corridor-like environment, a curve virtual tube with no obstacle inside was designed in our previous work. This article generalizes the controller design to the condition that all robots have self-localization drifts and precise relative navigation, where the flocking algorithm is introduced to reduce the negative impact of the self-localization drift. Similar to the "many wrongs principle," it is shown that the cohesion behavior and the velocity alignment behavior are able to reduce the influence of the position measurement drift and the velocity measurement error, respectively. For convenience in practical use, a modified vector field controller with five control terms is put forward. Finally, the effectiveness of the proposed method is validated by numerical simulations and real experiments.

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Section: Distributed Controller For Passing Through the Curve Virtual...mentioning

confidence: 99%

Section: Assumption 4 the Robots' Initial Conditions Satisfymentioning

confidence: 99%

Section: Analysis: Control Effectiveness Of Robust Swarm Controllermentioning

confidence: 99%

Section: Simulations To Show Effectiveness Of Robot Cohesion Term In ...mentioning

confidence: 99%

Section: Robot Kinematics Modelmentioning

confidence: 99%

See 3 more Smart Citations

Robust distributed control within a curve virtual tube for a robotic swarm under self‐localization drift and precise relative navigation

Gao

Bai

Quan

2023

Intl J Robust & Nonlinear

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Decentralized deconfliction of aerial robots in high intensity traffic structures

Crann,

Amiri,

Knox

et al. 2024

Journal of Field Robotics

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Projections for future air mobility envisage intensely utilized airspace that does not simply scale up from existing systems with centralized air traffic control. This paper considers the implementation and test of a software and hardware framework for decentralized control of aerial vehicles within intensely used airspace. Up to 10 rotary wing vehicles of maximum all up mass of are flown in an outdoor volume with length scale of with GPS and WiFi connectivity. Flight control is implemented using a Pixhawk 4 flight controller running the PX4 firmware with guidance algorithms run on a separate onboard companion computer. Deconfliction is implemented using a simple elastic repulsion model with a guidance update rate of . Traffic structures are constructed from a path of directed waypoints and associated cross sectional geometry. Junctions are implemented when two paths converge into one or when one path diverges into two. Agents engage with structures through execution of flow, merge and swirl velocity rules. Calibration experiments showed that the worst case latency in agents sharing position information was of the order of made up from delays due to finite guidance update rate, WiFi processing and centralized message processing. A choice of vehicle cruise speed of and conflict radius of provided an acceptable compromise between experiment time efficiency (speed) and spatial efficiency (resolution) within the test volume. Results from recirculating junction experiments show that peak deconfliction activity occurs at the junction node, however biased distribution of agents within a corridor means the peak intensity is pushed ahead of the node. Use of meshed helical junction structures significantly reduces the intensity of conflict at the expense of reduced junction time efficiency.

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Distributed Control of Heterogeneous Modular Flight Arrays under the Limited Space Constraints

Liu,

Yang,

Zhang

et al. 2024

2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS)

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Distributed control for a robotic swarm to pass through a curve virtual tube

Cited by 9 publications

References 37 publications

Robust distributed control within a curve virtual tube for a robotic swarm under self‐localization drift and precise relative navigation

Robust distributed control within a curve virtual tube for a robotic swarm under self‐localization drift and precise relative navigation

Decentralized deconfliction of aerial robots in high intensity traffic structures

Distributed Control of Heterogeneous Modular Flight Arrays under the Limited Space Constraints

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