Image-Based Multi-UAV Tracking System in a Cluttered Environment

Hung, Hsin-Ai; Hsu, Hao-Huan; Cheng, Teng-Hu

doi:10.1109/tcns.2022.3181255

Cited by 7 publications

(1 citation statement)

References 31 publications

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“…Similar solutions for this problem have been presented in the literature, however, there are some key differences to be considered. In [15], the authors face the problem of maintaining the continuous tracking of a target using a fleet of drones. They propose a multi-objective distributed optimization problem that ensures connectivity maintenance of the fleet, obstacle avoidance, and occlusion avoidance.…”

Section: A Related Work and Contributionsmentioning

confidence: 99%

Directed Graph Topology Preservation in Multi-Robot Systems With Limited Field of View Using Control Barrier Functions

Bertoncelli,

Radhakrishnan,

Catellani

et al. 2024

IEEE Access

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This paper addresses the crucial challenge of maintaining the directed graph topology in multi-robot systems, particularly when operating under limited field-of-view constraints and with a lack of communication among robots. Traditional methods for multi-robot coordination rely heavily on interrobot communication, which may not always be feasible, particularly in constrained or hostile environments. Our work presents a novel distributed control algorithm that leverages Control Barrier Functions (CBFs) to maintain the graph topology of a multi-robot system based solely on local, onboard sensor data. This approach is particularly beneficial in situations where external communication channels are disrupted or unavailable.The key contributions of this research are threefold: First, we design a novel control algorithm that efficiently maintains the graph topology in multi-robot systems using CBFs, which operate on neighbor detection data. Second, we perform an experimental evaluation of the algorithm, demonstrating its efficacy in controlling the flight of a team of drones using only local robot data. Third, we apply our methodology to a distributed coverage control scenario, showing that our approach can effectively manage a multi-robot system using only local information.

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Section: A Related Work and Contributionsmentioning

confidence: 99%