Bio-inspired vision mimetics toward next-generation collision-avoidance automation  

作　　者：Gary J.W.Xu Kun Guo Seop Hyeong Park Poly Z.H.Sun Aiguo Song 

机构地区：[1]Human Factors in Driving Lab,Huawei Technologies Co.,Ltd.,Shenzhen 518038,China [2]School of Psychology,University of Lincoln,Lincoln LN67TS,UK [3]School of Software,Hallym University,Chunchon Gangwon-do 24252,South Korea [4]School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China [5]School of Instrument Science and Engineering,Southeast University,Nanjing 210096,China

出　　处：《The Innovation》2023年第1期24-25,共2页创新（英文）

基　　金：supported in part by the EU’s Seventh Framework Program(EU FP7)International Research Staff Exchange Scheme(IRSES)Project-Towards zero road Accidents—Nature Inspired Hazard Perception under grant 318907;the Zhejiang Provincial Natural Science Foundation under grant LY23F030001.

摘　　要：MOTIVATION The current“deep learning+large-scale data+strong supervised labeling”technology framework of collision avoidance for ground robots and aerial drones is becoming saturated.Its development gradually faces challenges from real open-scene applications,including small data,weak annotation,and crossscene.Inspired by the neural structure and processes underlying human cognition(eg,human visual,auditory,and tactile systems)and the knowledge learned from daily driving tasks,a high-level cognitive system is developed for integrating collision sensing and collision avoidance.This bio-inspired cognitive approach has the advantages of good robustness,high self-adaptability,and low computation consumption in practical driving scenes.

关 键 词：COLLISION driving integrating 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]