Information-Driven Active Audio-Visual Source Localization.
We present a system for sensorimotor audio-visual source localization on a mobile robot. We utilize a particle filter for the combination of audio-visual information and for the temporal integration of consecutive measurements. Although the system only measures the current direction of the source, the position of the source can be estimated because the robot is able to move and can therefore obtain measurements from different directions. These actions by the robot successively reduce uncertainty about the source's position. An information gain mechanism is used for selecting the most informative actions in order to minimize the number of actions required to achieve accurate and precise position estimates in azimuth and distance. We show that this mechanism is an efficient solution to the action selection problem for source localization, and that it is able to produce precise position estimates despite simplified unisensory preprocessing. Because of the robot's mobility, this approach is suitable for use in complex and cluttered environments. We present qualitative and quantitative results of the system's performance and discuss possible areas of application.
Cognitive Neuroinformatics, Bremen University, Bremen, Germany.
Niclas
N
Schult
Cognitive Neuroinformatics, Bremen University, Bremen, Germany.
Thomas
T
Reineking
Cognitive Neuroinformatics, Bremen University, Bremen, Germany.
Thorsten
T
Kluss
Cognitive Neuroinformatics, Bremen University, Bremen, Germany.
Christoph
C
Zetzsche
D000465:Algorithms; D001185:Artificial Intelligence; D001303:Auditory Cortex / Q000502:physiology*; D004777:Environment; D012371:Robotics / Q000379:methods*; D014793:Visual Cortex / Q000502:physiology*