To move efficiently in an unknown or uncertain environment, a mobile robot must take observation from various sensors to provide information for path planning and execution. A sufficient representation of the external world would also be very useful for self-localization. One of the merits of applying multiple sensors to a mobile robot is the enhancement of environment recognition. In this paper, sensory information combined from double ultrasonic sensors and a CCD camera is provided for this purpose. We used ultrasonic sensors for distance measurement and a vision system for object boundaries detection. We developed an algorithm to eliminate errors due to the beam opening angle of ultrasonic sensors based on a dual-transducer design. Extended discrete Kalman filter was used to fuse raw sensory data and reduce the influence of specular reflection of ultrasonic type transducers. Therefore a more reliable representation was obtained for environment recognition. Computer simulation as well as practical experimental results show this sensory system can provide useful and robust environment recognition for intelligent robotics.
|Number of pages||8|
|State||Published - 1 Dec 1994|
|Event||Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems - Las Vegas, NV, USA|
Duration: 2 Oct 1994 → 5 Oct 1994
|Conference||Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems|
|City||Las Vegas, NV, USA|
|Period||2/10/94 → 5/10/94|