The auditory system is considered one of the crucial pathways for robots to perceive environmental information.The per-ception and decision-making capabilities of mobile robots are greatly enhanced by accurate and effective sound source localization,making it highly significant for applications in hazardous environment rescue and inspection.With the widespread adoption of deep learning,the effectiveness of sound source localization has been notably improved through the introduction of convolutional neural net-works(CNNs).Sound source localization for mobile robots was comprehensively compared and analyzed from four perspectives:net-work architecture and improvements,types of sound features,data simulation and augmentation,as well as the fusion of multimodal in-formation.Reflections and prospects on the application of the technology are also presented.
关键词
移动机器人/声源定位/卷积神经网络/麦克风阵列/到达方向估计
Key words
mobile robot/sound source localization/convolutional neural network/microphone array/direction of arrival
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