arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2002.12461cs.CVcs.LGcs.RO

Target Detection, Tracking and Avoidance System for Low-cost UAVs using AI-Based Approaches

School of Aerospace, Transport and Manufacturing, Cranfield University(克兰菲尔德大学航空、运输与制造学院);Cranfield University(克兰菲尔德大学)

Vinorth Varatharasan, Alice Shuang Shuang Rao, Eric Toutounji, Ju-Hyeon Hong, Hyo-Sang Shin

英文摘要:

An onboard target detection, tracking and avoidance system has been developed in this paper, for low-cost UAV flight controllers using AI-Based approaches. The aim of the proposed system is that an ally UAV can either avoid or track an unexpected enemy UAV with a net to protect itself. In this point of view, a simple and robust target detection, tracking and avoidance system is designed. Two open-source tools were used for the aim: a state-of-the-art object detection technique called SSD and an API for MAVLink compatible systems called MAVSDK. The MAVSDK performs velocity control when a UAV is detected so that the manoeuvre is done simply and efficiently. The proposed system was verified with Software in the loop (SITL) and Hardware in the loop (HITL) simulators. The simplicity of this algorithm makes it innovative, and therefore it should be used in future applications needing robust performances with low-cost hardware such as delivery drone applications.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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