Generating Robot-Dependent Cost Maps for Off-Road Environments Using Locomotion Experiments and Earth Observation Data

Matthias Josef Eder, Raphael Benjamin Prinz, Florian Schöggl, Gerald Steinbauer-Wagner

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


In recent years, the navigation capabilities of mobile robots in off-road environments have increased significantly, opening up new potential applications in a variety of settings. By accurately identifying different classes of terrain in unstructured environments, safe automated navigation can be supported. However, to enable safe path planning and execution, the traversability costs of the terrain classes need to be estimated. Such estimation is often performed manually by experts who possess information about the environment and are familiar with the capabilities of the robotic system. In this paper, we present an automated pipeline for generating traversability costs that use recorded locomotion data and descriptive information on the terrain obtained from earth observation data. The main contribution is that the cost estimation for different terrain classes is based on locomotion data obtained in simple standardized experiments. Moreover, by repeating the experiments with different robot systems we are easily able to identify the actual capabilities of that systems. Experiments were conducted in an alpine off-road environment to record locomotion data of four different robot systems and to investigate the performance and validity of the proposed pipeline. The recorded locomotion data for the different robots are publicly available at
Original languageEnglish
Title of host publication2022 Sixth IEEE International Conference on Robotic Computing (IRC)
PublisherIEEE Xplore
Number of pages5
Publication statusPublished - 2022

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