ROSYSep 15, 2021

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

arXiv:2109.07079v110 citations
Originality Incremental advance
AI Analysis

This addresses the problem of reliable multi-UAV tracking for applications like surveillance or search-and-rescue, though it appears incremental as it builds on existing control methods like CBFs.

The paper developed a tracking controller for multiple UAVs to cooperatively track a dynamic target in cluttered environments, ensuring the target remains in view while avoiding occlusions and collisions, with simulations demonstrating its efficacy.

A tracking controller for unmanned aerial vehicles (UAVs) is developed to track moving targets undergoing unknown translational and rotational motions. The main challenges are to control both the relative positions and angles between the target and the UAVs to within desired values, and to guarantee that the generated control inputs to the UAVs are feasible (i.e., within their motion capabilities). Moreover, the UAVs are controlled to ensure that the target always remains within the fields of view of their onboard cameras. To the best of our knowledge, this is the first work to apply multiple UAVs to cooperatively track a dynamic target while ensuring that the UAVs remain connected and that both occlusion and collisions are avoided. To achieve these control objectives, a designed controller solved based on the aforementioned tracking controller using quadratic programming can generate minimally invasive control actions to achieve occlusion avoidance and collision avoidance. Furthermore, control barrier functions (CBFs) with a distributed design are developed in order to reduce the amount of inter-UAV communication. Simulations were performed to assess the efficacy and performance of the developed CBF-based controller for the multi-UAV system in tracking a target.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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