8 citations · 9 across the 5 of their papers we have counts for
7 papers
Long-term map maintenance pipeline for autonomous vehicles
Julie Stephany Berrio, Stewart Worrall, Mao Shan +1
For autonomous vehicles to operate persistently in a typical urban environment, it is essential to have high accuracy position information. This requires a mapping and localisation…
Camera-Lidar Integration: Probabilistic sensor fusion for semantic mapping
Julie Stephany Berrio, Mao Shan, Stewart Worrall +1
An automated vehicle operating in an urban environment must be able to perceive and recognise object/obstacles in a three-dimensional world while navigating in a constantly changin…
Probabilistic Egocentric Motion Correction of Lidar Point Cloud and Projection to Camera Images for Moving Platforms
Mao Shan, Julie Stephany Berrio, Stewart Worrall +1
The fusion of sensor data from heterogeneous sensors is crucial for robust perception in various robotics applications that involve moving platforms, for instance, autonomous vehic…
Semantic sensor fusion: from camera to sparse lidar information
Julie Stephany Berrio, Mao Shan, Stewart Worrall +2
To navigate through urban roads, an automated vehicle must be able to perceive and recognize objects in a three-dimensional environment. A high-level contextual understanding of th…
Automatic extrinsic calibration between a camera and a 3D Lidar using 3D point and plane correspondences
Surabhi Verma, Julie Stephany Berrio, Stewart Worrall +1
This paper proposes an automated method to obtain the extrinsic calibration parameters between a camera and a 3D lidar with as low as 16 beams. We use a checkerboard as a reference…
Automated Evaluation of Semantic Segmentation Robustness for Autonomous Driving
Wei Zhou, Julie Stephany Berrio, Stewart Worrall +1
One of the fundamental challenges in the design of perception systems for autonomous vehicles is validating the performance of each algorithm under a comprehensive variety of opera…