Shaozu Cao
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View article: A General Optimisation‐Based Framework for Global Pose Estimation With Multiple Sensors
A General Optimisation‐Based Framework for Global Pose Estimation With Multiple Sensors Open
Accurate state estimation is a fundamental problem for autonomous robots. To achieve locally accurate and globally drift‐free state estimation, multiple sensors with complementary properties are usually fused together. Local sensors (camer…
View article: GVINS: Tightly Coupled GNSS–Visual–Inertial Fusion for Smooth and Consistent State Estimation
GVINS: Tightly Coupled GNSS–Visual–Inertial Fusion for Smooth and Consistent State Estimation Open
Visual–inertial odometry (VIO) is known to suffer from drifting, especially over long-term runs. In this article, we present GVINS, a nonlinear optimization-based system that tightly fuses global navigation satellite system (GNSS) r…
View article: GVINS: Tightly Coupled GNSS-Visual-Inertial Fusion for Smooth and Consistent State Estimation
GVINS: Tightly Coupled GNSS-Visual-Inertial Fusion for Smooth and Consistent State Estimation Open
Visual-Inertial odometry (VIO) is known to suffer from drifting especially over long-term runs. In this paper, we present GVINS, a non-linear optimization based system that tightly fuses GNSS raw measurements with visual and inertial infor…
View article: A General Optimization-based Framework for Local Odometry Estimation with Multiple Sensors
A General Optimization-based Framework for Local Odometry Estimation with Multiple Sensors Open
Nowadays, more and more sensors are equipped on robots to increase robustness and autonomous ability. We have seen various sensor suites equipped on different platforms, such as stereo cameras on ground vehicles, a monocular camera with an…
View article: A General Optimization-based Framework for Global Pose Estimation with Multiple Sensors
A General Optimization-based Framework for Global Pose Estimation with Multiple Sensors Open
Accurate state estimation is a fundamental problem for autonomous robots. To achieve locally accurate and globally drift-free state estimation, multiple sensors with complementary properties are usually fused together. Local sensors (camer…
View article: Understanding Hidden Memories of Recurrent Neural Networks
Understanding Hidden Memories of Recurrent Neural Networks Open
Recurrent neural networks (RNNs) have been successfully applied to various natural language processing (NLP) tasks and achieved better results than conventional methods. However, the lack of understanding of the mechanisms behind their eff…