Optimal coding for naturally occurring whisker deflections
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Biomimetic whiskers for shape recognition
Robotics and Autonomous Systems
A general classifier of whisker data using stationary naive bayes: application to BIOTACT robots
TAROS'11 Proceedings of the 12th Annual conference on Towards autonomous robotic systems
CrunchBot: a mobile whiskered robot platform
TAROS'11 Proceedings of the 12th Annual conference on Towards autonomous robotic systems
Mapping with sparse local sensors and strong hierarchical priors
TAROS'11 Proceedings of the 12th Annual conference on Towards autonomous robotic systems
Towards hierarchical blackboard mapping on a whiskered robot
Robotics and Autonomous Systems
Animal vibrissae: modeling and adaptive control of bio-inspired sensors
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advences in computational intelligence - Volume Part II
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Sensing in the dark is a useful but challenging task both for biological agents and robots. Rats and mice use whiskers for the active exploration of their environment. We have built a robot equipped with two active whisker arrays and tested whether they can provide reliable texture information. While it is relatively easy to classify data recorded at a specified distance and angle to the object, it is more challenging to achieve texture discrimination on a mobile robot. We used a standard neural network classifier to show that it is in principle possible to discriminate textures using whisker sensors even under real-world conditions.