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  • 标题:Self-Supervised Learning of Motion-Induced Acoustic Noise Awareness in Social Robots
  • 本地全文:下载
  • 作者:João Andrade ; Pedro Santana ; Alexandre P. Almeida
  • 期刊名称:Journal of Automation, Mobile Robotics & Intelligent Systems (JAMRIS)
  • 印刷版ISSN:1897-8649
  • 电子版ISSN:2080-2145
  • 出版年度:2019
  • 卷号:13
  • 期号:1
  • 页码:3-13
  • DOI:10.14313/JAMRIS_1-2019/1
  • 出版社:Industrial Research Inst. for Automation and Measurements, Warsaw
  • 摘要:With the growing presence of robots in human populatedenvironments, it becomes necessary to render theirpresence natural, rather than invasive. To do that, robotsneed to make sure the acous􀆟c noise induced bytheir mo􀆟on does not disturb people nearby. 􀀯n this line,this paper proposes a method that allows the robot tolearn how to control the amount of noise it produces,taking into account the environmental context and therobot’s mechanical characteris􀆟cs. 􀀒oncretely, the robotadapts its mo􀆟on to a speed that allows it to produceless noise than the environment’s background noise and,hence, avoiding to disturb nearby humans. For that, beforeexecu􀆟ng any given task in the environment, the robotlearns how much acous􀆟c noise it produces at di􀄫erentspeeds in that environment by gathering acous􀆟c informa􀆟on through a microphone. The proposed methodwas successfully validated on various environments withvarious background noises. 􀀯n addi􀆟on, a 􀁗􀀯􀁚 sensor wasinstalled on the robot in order to test the robot’s ability totrigger the noise-aware speed control procedure when aperson enters the sensor’s field of view. The use of a sucha simple sensor aims at demonstra􀆟ng the ability of theproposed system to be deployed in minimalis􀆟c robots,such as micro unmanned aerial vehicles.
  • 关键词:Social 􀁚obots; 􀀄cous􀆟c 􀁅oise; 􀁄o􀆟on 􀀒ontrol;Self-Supervised Learning
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