University of Birmingham > Talks@bham > Artificial Intelligence and Natural Computation seminars > Robot Audition for Situational Awareness

Robot Audition for Situational Awareness

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Host: Dr Mohan Sridharan (M.Sridharan@bham.ac.uk)

Abstract: Sound is used in nature to detect, identify and track salient events, to navigate, and to self-localise. The ability to make sense of acoustic signals is therefore a fundamental prerequisite for robots and autonomous systems. Audition – the ability to hear – excels particularly in scenarios where lighting conditions are poor, where salient events are outside of the line-of-sight, and in crowded environments where sensors, such as LIDAR and RADAR , are unreliable. However, due to the challenges affecting acoustic signals, robot audition has, to date, received only limited attention in the research community.

This talk focuses on acoustic scene mapping for robot audition in order to address the questions: “What is around me?” and “Where am I?”. The first part of the talk addresses the practical challenges of tracking moving sound sources when microphone arrays are integrated on moving platforms. The second part addresses the self-localization of the moving microphone array in the acoustic scene map when prior knowledge of the array position and orientation are unavailable. To conclude, extensions, including multi-modal sensor fusion, and future directions are discussed.

Biography: Christine Evers is an EPSRC research fellow in the Department of Electrical and Electronic Engineering at Imperial College London. Her research focuses on robot audition in order to equip robots and autonomous agents with the ability to make sense of their acoustic environments. She received her PhD from the University of Edinburgh, UK, in 2010. After a position as a research fellow at the University of Edinburgh between 2009 and 2010, she worked as a senior systems engineer at the defence company, Selex Electronic Systems, Edinburgh, UK, between 2010 and 2014. She returned to academia as a research associate at Imperial College on the EU FP7 project “Embodied Audition for Robots” in 2014. In 2017, she was awarded a fellowship by the UK Engineering and Physical Research Council (EPSRC) to advance her research on robot audition. Christine is an IEEE Senior Member, a member of the IEEE Technical Committee on Audio and Acoustic Signal Processing, and serves as an associate editor of the EURASIP Journal on Audio, Speech, and Music Processing.

Website: https://www.imperial.ac.uk/people/c.evers

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

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