Title :
Learning to locate an odour source with a mobile robot
Author :
Duckett, Tom ; Axelsson, Mikael ; Saffiotti, Alessandro
Author_Institution :
Dept. of Techol., Orebro Univ., Sweden
Abstract :
We address the problem of enabling a mobile robot to locate a stationary odour source using an electronic nose constructed from gas sensors. On the hardware side, we use a stereo nose architecture consisting of two parallel chambers, each containing an identical set of sensors. On the software side, we use a recurrent artificial neural network to learn the direction to a stationary source from a time series of sensor readings. This contrasts with previous approaches, that rely on the existence of a model of the sensor´s dynamics. The complete system is able to orient and turn towards the source. An experimental validation was carried out to evaluate the performance of the system.
Keywords :
gas sensors; learning (artificial intelligence); mobile robots; position control; recurrent neural nets; time series; electronic nose; gas sensors; learning; mobile robot; odour source location; recurrent neural network; stereo nose architecture; time series; Artificial neural networks; Computer architecture; Delay; Electronic noses; Gas detectors; Hardware; Mobile robots; Sensor phenomena and characterization; Sensor systems; Solid state circuits;
Conference_Titel :
Robotics and Automation, 2001. Proceedings 2001 ICRA. IEEE International Conference on
Print_ISBN :
0-7803-6576-3
DOI :
10.1109/ROBOT.2001.933245