English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Mapping and localization is a critical module of autonomous driving, andsignificant achievements have been reached in this field. Beyond GlobalNavigation Satellite System (GNSS), research in point cloud registration,visual feature matching, and inertia navigation has greatly enhanced theaccuracy and robustness of mapping and localization in different scenarios.However, highly urbanized scenes are still challenging: LIDAR- and camera-basedmethods perform poorly with numerous dynamic objects; the GNSS-based solutionsexperience signal loss and multipath problems; the inertia measurement units(IMU) suffer from drifting. Unfortunately, current public datasets either donot adequately address this urban challenge or do not provide enough sensorinformation related to mapping and localization. Here we present UrbanLoco: amapping/localization dataset collected in highly-urbanized environments with afull sensor-suite. The dataset includes 13 trajectories collected in SanFrancisco and Hong Kong, covering a total length of over 40 kilometers. Ourdataset includes a wide variety of urban terrains: urban canyons, bridges,tunnels, sharp turns, etc. More importantly, our dataset includes informationfrom LIDAR, cameras, IMU, and GNSS receivers. Now the dataset is publiclyavailable through the link in the footnote. Dataset Link:https://advdataset2019.wixsite.com/urbanloco.

UrbanLoco: A Full Sensor Suite Dataset for Mapping and Localization in Urban Scenes