Planning for real robots to act in dynamic and uncertain environments is a challenging problem. A complete model of the world is not viable and an integration of deliberation and ...
Manuela M. Veloso, Elly Winner, Scott Lenser, Jame...
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and ...
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...
Learning the knowledge of scene structure and tracking a large number of targets are both active topics of computer vision in recent years, which plays a crucial role in surveilla...
Xuan Song, Xiaowei Shao, Huijing Zhao, Jinshi Cui,...
In this paper, we present a framework for a robotic system with the ability to perform real-world manipulation tasks. The complexity of such tasks determines the precision and fre...
Danica Kragic, Lars Petersson, Henrik I. Christens...