Autonomous boats perception methods

Researchers

Matej Kristan, PhD
Matej Kristan, PhD

Low-end small unmanned surface vehicles (USV) are higly agile machines ideal for patrolling coastal waters. Such vehicles are typically used in perimeter surveillance, in which the USV travels along a pre-planned path. To quickly and efficiently respond to the challenges from highly dynamic environment, the USV requires an onboard logic to observe the surrounding, detect potentially dangerous situations, and apply proper route modifications. This page is a collection of algorithms and approaches that we have developed for such machines.

Projects

DAViMaRAdaptive deep perception methods for autonomous surface vehicles

April 2020 - August 2023
The project primary goal is to develop the next-generation maritime environment perception methods, which will harvest the power of end-to-end trainable deep models for essential challenges of safe operation like: general obstacle detection with re-identification, implicit detection of hazardous areas and sensor fusion for improved detection.

ViAMaRoRobust computer vision methods for autonomous water surface vehicles

May 2017 - April 2020
The project primary goal is to develop functionalities required for robust autonomous navigation of USVs in uncontrolled environments, primarily relying on the captured visual information. The project focuses on obstacle detection using monocular and stereo systems, development of efficient visual tracking algorithms for marine environments and environment representation through sensor fusion.

Publications