title: Sound Source Localization in Complex Indoor Environment: A Self-Supervised Incremental Learning Approach
abstract: Sound source localization is essential in robotics, which broadens the possibilities of human-robot interactions by enriching the robot's perceptual capabilities. Localizing an acoustic source in a complex indoor environment is especially challenging due to the high noise-to-signal ratio and reverberations. In this thesis, we present an incremental learning framework for mobile robots localizing the human sound source using a microphone array in a complex indoor environment consisting of multipl
journal: eScholarship (California Digital Library)