Outputs
In the Computational Robotics Laboratory (CRL/ComRob), our research has delivered practical algorithmic and system-level results that push autonomy from controlled demos to real deployments. We have contributed new methods for mission planning and routing in multi-goal data-collection tasks (including TSP/TSPN-style formulations and robust variants), enabling autonomous robots to gather information efficiently under real-world constraints. We have also produced learning-driven autonomy results—e.g., unsupervised/self-organizing representations that adapt online to prioritize sensing targets and scale to complex environments—supporting long-duration operations and adaptive decision-making. In parallel, CRL advances resilient navigation and control, including work spanning GNSS-denied operation, sensor fusion/SLAM-oriented autonomy themes, and agile control for aerial and legged systems—bridging theory with field-ready robotic platforms used across the lab.
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Autonomous Industrial Patrol Ground Robotics System
The system is a cyber-physical stack for autonomous patrolling of industrial sites using ground robots, combining global and local perception to enable reliable operation in dynamic environments. The main computing unit is a compact industrial PC with multiple Ethernet interfaces, enabling separation of sensing subsystems into independent networks and supporting high-bandwidth data streaming. Navigation and obstacle perception are based on multiple 3D ranging sensors, complemented by a multi-constellation satellite-based positioning system with redundant antennas for robust and accurate localization. Vision sensors provide high-resolution visual data for object detection and classification, while a cellular communication module ensures low-latency, high-throughput connectivity with the control center for real-time data and video transmission.
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5G Dataset 2025 Freyung
Collected RSRP measurement of the indoor private 5G infrastructure of the DIT building in Freyung. The data are collected by a mobile robot Husky A200 and georeferenced using SLAM with 3D LiDAR measurements. The datasets include created 3D environment model and collected RSRP values with the frequencey of 1 Hz along the robot path.
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Functional Sample of a Mobile Robotic Sensing System with Multi-Channel Communication and Signal Monitoring
The functional sample represents a system consisting of mobile ground robotic units and a communication base station that can integrate a private local communication infrastructure, such as 4G/LTE mesh networking, 5G, or LoRa technologies. The mobile robots are capable of operating in both indoor and outdoor environments without reliance on GNSS availability and are able to collect robotic sensing data, including 3D point clouds from range sensors and RGB image data, which can be transmitted to the base station in real time. The system integrates robotic mobility, environmental sensing, and measurement of multiple communication signals to support situational awareness and reliable data exchange during mission execution. It enables real-time acquisition, processing, and transmission of operational and telemetry data to remote command and control centers. The functional sample demonstrates operation over heterogeneous communication channels, including scenarios outside standard public network coverage. It incorporates methods for situational awareness and serves as a validation platform for integrated sensing, communication, and data-sharing capabilities under realistic operational conditions.
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