Self-Supervised Learning of Motion-Induced Acoustic Noise Awareness in Social Robots

João Andrade, Pedro Santana, Alexandre P. Almeida
2019 Journal of Automation, Mobile Robotics & Intelligent Systems  
With the growing presence of robots in human populated environments, it becomes necessary to render their presence natural, rather than invasive. To do that, robots need to make sure the acous�c noise induced by their mo�on does not disturb people nearby. �n this line, this paper proposes a method that allows the robot to learn how to control the amount of noise it produces, taking into account the environmental context and the robot's mechanical characteris�cs. �oncretely, the robot adapts its
more » ... mo�on to a speed that allows it to produce less noise than the environment's background noise and, hence, avoiding to disturb nearby humans. For that, before execu�ng any given task in the environment, the robot learns how much acous�c noise it produces at di�erent speeds in that environment by gathering acous�c in-forma�on through a microphone. The proposed method was successfully validated on various environments with various background noises. �n addi�on, a ��� sensor was installed on the robot in order to test the robot's ability to trigger the noise-aware speed control procedure when a person enters the sensor's field of view. The use of a such a simple sensor aims at demonstra�ng the ability of the proposed system to be deployed in minimalis�c robots, such as micro unmanned aerial vehicles.
doi:10.14313/jamris_1-2019/1 fatcat:w7gfhvopxrbhfjamlsh5cnnghi