Auditory Evidence Grids

Sound source localization on a mobile robot can be a difficult task due to a variety of problems inherent to a real environment, including robot ego-noise, echoes, and the transient nature of ambient noise. As a result, source localization data are often very noisy and unreliable. In this work, we overcome some of these problems by combining the localization evidence over a variety of robot poses using an evidence grid. The result is a representation that localizes the pertinent objects well over time, can be used to filter poor localization results, and may also be useful for global re-localization from sound localization results

Authors

• Eric Martinson
• Alan C. Schultz

Keywords

• Mobile robots
• Working environment noise
• Acoustic noise
• Microphone arrays
• Noise level
• Intelligent robots
• Filters
• Fans
• Acoustic sensors
• Mirrors
• Mobile Robot
• Sound Source
• Sound Localization
• Robot Pose
• Local Environment
• Single Measurement
• Ventilator
• Cross-correlation
• Grid Cells
• Types Of Sources
• Indoor Environments
• Environmental Sources
• Speed Of Sound
• Environmental Noise
• Static Position
• Audio Data
• Soundscape
• Tape Recorder
• Ambient Noise Levels
• Global Coordinates
• Microphone Array
• Center Of The Array
• Noise Map
• Robot Base
• Local Algorithm
• Fewer Samples
• Sensor Measurements
• Time Difference
• Laser Ranging
• Spatial Measures
• Sound Source Localization
• Evidence Grid
• Auditory Mapping