Improving Monocular SLAM: using Depth Estimating CNN

To bring down the number of traffic accidents and increase people’s mobility companies, such as Robot Engineering Systems (RES) try to put automated vehicles on the road. RES is developing the WEpod, a shuttle capable of autonomously navigating through mixed traffic. This research has been done in cooperation with RES to improve the localization...

Evaluating SLAM in an urban dynamic environment

Simultaneous Localization And Mapping (SLAM) algorithms provide accurate localization for autonomous vehicles and provide essential information for the path planning module. However, SLAM algorithms as- sume a static environment in order to estimate a location. This assumption influences the pose estimation in dynamic urban environments. The...

On the robustness of ORB matching in feature-based SLAM

A robotic vehicle must continuously determine its position within the map to traverse a path safely; this is called self-localization. Current localization methods use mainly sensors like LIDARS. However, a LIDAR does not return data points if the environment is an empty field; the laser scan of the LIDAR does not reflect without obstacles,...