Accurate sensor calibration is a prerequisite for autonomous vehicles' multi-sensor
perception. Even though there are many open-source projects related to sensor calibration …

As solid-state LiDAR technology advances, mobile robotics and autonomous driving
increasingly rely on multiple solid-state LiDARs for perception. However, limited or non …

Recent RGB-D semantic segmentation networks are usually manually designed. However,
due to limited human efforts and time costs, their performance might be inferior for complex …

State-of-the-art LiDAR calibration frameworks mainly use non-probabilistic registration
methods such as Iterative Closest Point (ICP) and its variants. These methods suffer from …

With the development of autonomous driving, more autonomous vehicles are equipped with
multiple sensors to perform better. For multi-sensor systems, accurate extrinsic calibration is …

Multi-sensor fusion is important in the field of autonomous driving. A basic prerequisite for
multi-sensor fusion is calibration between sensors. Such calibrations must be accurate and …

Sensor-based environmental perception is a crucial component of autonomous driving
systems. To perceive the surrounding environment better, an intelligent system would utilize …

In the realm of autonomous driving, there is a pressing demand for heightened perceptual
capabilities, giving rise to a plethora of multisensory solutions. Among these, multi-LiDAR …

Autonomous systems often employ multiple LiDARs to leverage the integrated advantages,
enhancing perception and robustness. The most critical prerequisite under this setting is the …

Modern autonomous systems typically use several sensors for perception. For best
performance, accurate and reliable extrinsic calibration is necessary. In this research, we …