Future vehicles:learnable wheeled robots  

作　　者：Deyi LI Nan MA Yue GAO 

机构地区：[1]Academy of Military Science,Beijing 100036,China [2]Beijing Key Laboratory of Information Service Engineering,Beijing Union University,Beijing 100101,China [3]College of Robotics,Beijing Union University,Beijing 100101,China [4]School of Software,Tsinghua University,Beijing 100084,China

出　　处：《Science China(Information Sciences)》2020年第9期245-252,共8页中国科学（信息科学）（英文版）

基　　金：National Natural Science Foundation of China(Grant Nos.61871038;61931012);Beijing Natural Science Foundation(Grant No.4182022);Major project of Beijing Social Science Foundation(Grant No.18ZDA09)。

摘　　要：As one of the important signs of the third wave of artificial intelligence,wheeled robots not only inherit knowledge but also learn independently,which brings about to learnable wheeled robots that use a driving brain to achieve data-driven control and learning.Presently,most existing technologies for selfdriving vehicles can learn positively from the benchmark drivers to guarantee safe driving.However,in many unpredicted situations,such as rollover,human drivers often cause the behavior of irrational subconscious on account of human emotions like panic.In this paper,we propose a learnable wheeled robot using the driving brain by taking the rollover as an example,which is the most serious and dangerous situation in dynamic vehicle operations.Then,based on the analysis of rollover accidents,we utilize the driving brain reversely and conduct negative learning,materializing,and condensing the group intelligence of accident experts,to solve the problem of the lack of individual intelligence in emergencies and further promote real-time response to other dangerous conditions,such as puncture for self-driving vehicles.

关 键 词：wheeled robots driving brain swarm intelligence negative learning data-driven self-learning 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] U463.6[自动化与计算机技术—控制科学与工程]