KVHhome
KVHhome

FinnForest Dataset: A forest landscape for visual SLAM


FinnForest Dataset: A forest landscape for visual SLAM using KVH’s 1750 IMU

With the intense interest in developing safe, marketable self-driving vehicles, many companies are focused on the advantages that autonomous vehicles could bring to industries such as mining, shipping, agriculture, and forestry. Simultaneous Localization and Mapping (SLAM) is one tool being used to explore how to improve autonomous navigation performance. This paper by researchers at the University of Tampere, Finland, presents a SLAM dataset carried out in challenging suburban and forest environments. 

This white paper discusses: 

  • Challenges faced by autonomous vehicles in precise navigation when the environment is obstructed by natural terrain

  • How inertial navigation helped to overcome the obstacles that GNSS alone could not