—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....
Sampling multisensory information and taking the appropriate motor action is critical for a biological organism’s survival, but a difficult task for robots. We present a Neurally...
This paper describes a localization system for mobile robots moving in dynamic indoor environments, which uses probabilistic integration of visual appearance and odometry informat...
Nicola Bellotto, Kevin Burn, E. Fletcher, Stefan W...
— This paper describes an off-line, iterative algorithm for simultaneous localization and mapping within large indoor environments. The proposed approach is based on the idea of ...
In this paper, we consider a hybrid solution to the sensor network position inference problem, which combines a real-time filtering system with information from a more expensive,...
Dimitri Marinakis, David Meger, Ioannis M. Rekleit...