Acous&c&Propriocep&veSensing onOutdoorMobileRobotsfor - - PowerPoint PPT Presentation
Acous&c&Propriocep&veSensing onOutdoorMobileRobotsfor ObjectRecogni&on DebadeeptaDey HatemAlismail JacquelineLibby MainIdea DirtRoad HardRoad Gravel
Acous&c Propriocep&ve Mobile robot interacts with environment Dirt Road Hard Road Gravel Short grass Tall grass Small rock Large rock Bush Pile of leaves ScaIered leaves Bramble Puddles Mud Classifiers
Acous&c Bag of words SVM Neural Networks Dirt Road Hard Road Gravel Short grass Tall grass Small rock Large rock Bush Pile of leaves ScaIered leaves Bramble Puddles Mud Feature Extrac&on
Classifica&on Noise filtering Raw Data Proprio‐ cep&ve
from 3D Data and Audio. Pages 336–341. Proceedings of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 2006.
– Signal processing to classify func&onal components of objects
Terrain Characteriza&on and Classifica&on with a Mobile Robot. Journal of Field Robo&cs, 23(2):103–122, 2006.
– Gravel, grass, sand, pavement, dirt – Gyros, accelerometers, encoders, motor current and voltage sensors, ultrasonic, infrared microphones – One NN for each modality, then compared – Gyros ‐> road type: gravel, pavement, or dirt – Microphones ‐> grass, not grass