Multi-sensor fusion is for enhancing environment perception and 3D reconstruction in self-
driving and robot navigation. Calibration between sensors is the precondition of effective …

This paper investigates a novel calibration process of devices with different modalities,
which is a critical step of computer vision applications. We propose a fully automatic extrinsic …

Multi-sensor solution has been widely adopted in real-world robotics systems (eg, self-
driving vehicles) due to its better robustness. However, its performance is highly dependent …

Recent progress in the automated driving system and advanced driver assistant system has
shown that the combined use of 3D light detection and ranging (LiDAR) and the camera is …

Modern visual perception techniques often rely on multiple heterogeneous sensors to
achieve accurate and robust estimates. Knowledge of their relative positions is a mandatory …

In this paper we propose an end-to-end, automatic, online camera-LIDAR calibration
approach, for application in self driving vehicle navigation. The main idea is to connect the …

Current traditional methods for LiDAR-camera extrinsics estimation depend on offline targets
and human efforts, while learning-based approaches resort to iterative refinement for …

Low cost 3D LiDAR complements cameras in perception algorithms for various robotic
applications. Safe and efficient human robot collaboration requires easy and accurate …

The problem of non-Gaussian noise/outliers has been intrinsic in modern Simultaneous
Localization and Mapping (SLAM) applications. Despite numerous algorithms in SLAM, it …

Automated systems are equipped with an increasing number of diverse sensors to deal with
more and more complex tasks. Accurate sensor calibration is an essential prerequisite for …