With the significant development of practicability in deep learning and the ultra-high-speed
information transmission rate of 5G communication technology will overcome the barrier of …

Autonomous driving of higher automation levels asks for optimal execution of critical
maneuvers in all environments. A crucial prerequisite for such optimal decision-making …

We address joint extrinsic calibration of lidar, camera and radar sensors. To simplify
calibration, we propose a single calibration target design for all three modalities, and …

We present a novel open-source tool for extrinsic calibration of radar, camera and lidar.
Unlike currently available offerings, our tool facilitates joint extrinsic calibration of all three …

As a crucial step of sensor data fusion, sensor calibration plays a vital role in many cutting-
edge machine vision applications, such as autonomous vehicles and AR/VR. Existing …

The demand for multimodal sensing systems for robotics is growing due to the increase in
robustness, reliability and accuracy offered by these systems. These systems also need to …

In this paper, we present a probabilistic framework to recover the extrinsic calibration
parameters of a lidar-IMU sensing system. Unlike global-shutter cameras, lidars do not take …

Driving scene understanding is an essential technique for realizing autonomous driving.
Although many large-scale datasets for autonomous driving have enabled studies in terms …

Collision avoidance is an important feature in advanced driver-assistance systems, aimed at
providing correct, timely and reliable warnings before an imminent collision (with objects …

With the rapid development of autonomous driving and SLAM technology, the perception
system of a vehicle heavily relies on laser and image sensors to capture the real-world …