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

Visual place recognition and simultaneous localization and mapping (SLAM)have recently begun to be used in real-world autonomous navigation tasks likefood delivery. Existing datasets for SLAM research are often not representativeof in situ operations, leaving a gap between academic research and real-worlddeployment. In response, this paper presents the Segway DRIVE benchmark, anovel and challenging dataset suite collected by a fleet of Segway deliveryrobots. Each robot is equipped with a global-shutter fisheye camera, aconsumer-grade IMU synced to the camera on chip, two low-cost wheel encoders,and a removable high-precision lidar for generating reference solutions. Asthey routinely carry out tasks in office buildings and shopping malls whilecollecting data, the dataset spanning a year is characterized by planarmotions, moving pedestrians in scenes, and changing environment and lighting.Such factors typically pose severe challenges and may lead to failures for SLAMalgorithms. Moreover, several metrics are proposed to evaluate metric placerecognition algorithms. With these metrics, sample SLAM and metric placerecognition methods were evaluated on this benchmark.  The first release of our benchmark has hundreds of sequences, covering morethan 50 km of indoor floors. More data will be added as the robot fleetcontinues to operate in real life. The benchmark is available athttp://drive.segwayrobotics.com/#/dataset/download.

Segway DRIVE Benchmark: Place Recognition and SLAM Data Collected by A Fleet of Delivery Robots