Master's Thesis - Localization of Mobile Tracked Robots in Open Areas Using Remote Visual Features

Call for applications for disciplines such as: electrical engineering, computer science, control systems, or related fields. In the "Navigation mobile Robots" research group, we develop autonomous outdoor robots such as tracked platforms for applications in exploration, agriculture, and forestry, capable of independently traversing vast terrains. The group focuses on developing both the robots themselves and the autonomy stack that powers them. Outdoor robots operating in large open areas (e.g., airports, agricultural sites, or remote coastal regions) face a fundamental limitation: LiDAR-based localization degrades in open spaces due to a lack of geometric features, while GNSS/RTK signals are not always available or reliable. Consequently, missions must either be interrupted or continue with uncontrolled, accumulating drift. The objective of this thesis is to develop and evaluate a "bridging" localization method that enables the robot to continue its mission even in areas where LiDAR localization degrades. The approach combines multiple sources of information: • Distant visual features or those visible on the horizon, potentially captured and referenced automatically during the initial phase of the mission when LiDAR localization was reliable • Semantic image features derived from foundation models, where applicable, to ensure robust (context-aware) recognition of these visual features • The robot's proprioceptive sensors: IMU, odometry/encoders • The robot's planned movement patterns, serving as a trajectory prior