To fully utilize the information from the sensors, this paper proposes a new sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable an accurate measurement.
Exploration of an unknown environment is an important task for the new generation of mobile service robots. The mobile robots may navigate by means of a number of monitoring systems
such as the sonar-sensing system or the visual-sensing system. Note that in the conventional fusion schemes, the measurement is dependent on the current data sets only. Therefore, more of sensors are required to measure a certain physical parameter or to improve the accuracy of the measurement. However, in this approach, instead of adding more sensors to the system, the temporal sequence of the data sets are stored and utilized for the accurate measurement. The theoretical basis is illustrated by examples and the effectiveness is proved through the simulations and experiments. The newly proposed, STSF (Space and Time Sensor Fusion) scheme is applied to the navigation of a mobile robot in an unstructured environment, as well as in structured environment, and the experimental results show the performance of the system.
A Method of Planning Movement and Observation for a Mobile Robot Considering Uncertainties of Movement, Visual Sensing, and a Map.
