—Our sensor selection algorithm targets the problem of global self-localization of multi-sensor mobile robots. The algorithm builds on the probabilistic reasoning using Bayes fil...
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L....
Abstract. The Scale Invariant Feature Transform (SIFT) has become a popular feature extractor for vision-based applications. It has been successfully applied to metric localization...
In this paper we discuss landmark based absolute localization of tiny autonomous mobile robots in a known environment. Landmark features are naturally occurring as it is not allow...
The paper presents a new technique for extracting symbolic ground facts out of the sensor data stream in autonomous robots for use under hybrid control architectures, which compris...
:We present a comparison of an extended Kalman lter and an adaptation of bundle adjustment from computer vision for mobile robot localization and mapping using a bearing-only senso...