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基于 AI 芯片和机器视觉的协同控制实现

Translated title of the contribution: Implementation of Collaborative Control Based on AI Chips and Machine Vision
  • Cheng Wang
  • , Zhenrui Zhang
  • , Chao Fang
  • , Linna Wang
  • , Baochang Zhang*
  • *Corresponding author for this work
  • Beihang University
  • Shenzhen Academy of Aerospace Technology
  • China Aerospace Science and Technology Corporation

Research output: Contribution to journalArticlepeer-review

Abstract

Currently, there are few studies on how to realize autonomous navigation of unmanned cluster system in a networkless and GPS - free environment. For this special application scenario, this paper innovatively proposes a ground - air cooperative control system using a centralized formation approach based on machine vision. The system consists of air reconnaissance aircrafts, air - following aircrafts, ground reconnaissance vehicles and ground - following vehicles. The air reconnaissance aircrafts use VINS - MONO to navigate and provide a position reference. At the same time, the CVM - Net is used to match captured images of air reconnaissance aircrafts and ground reconnaissance vehicles to obtain the relative position of them, which is used to guide the ground - following vehicles and air reconnaissance vehicles, and YOLO - LITE detection algorithm is used to realize target real - time detection. The system uses Huawei Kirin 970 as the core hardware, which can realize real - time and no - return processing of information. Through this system, the ground and air unmanned cluster can perform autonomous navigation and coordinated control in the networkless and GPS - free environment, which has broad application prospects in the fields of emergency search and rescue and military investigation.

Translated title of the contributionImplementation of Collaborative Control Based on AI Chips and Machine Vision
Original languageChinese (Traditional)
Pages (from-to)67-73
Number of pages7
JournalAero Weaponry
Volume27
Issue number6
DOIs
StatePublished - 31 Dec 2020

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