Back to Search Start Over

Traversability analysis for off-road environments using locomotion experiments and earth observation data.

Authors :
Eder, Matthias
Prinz, Raphael
Schöggl, Florian
Steinbauer-Wagner, Gerald
Source :
Robotics & Autonomous Systems. Oct2023, Vol. 168, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

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 types 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 types need to be accurately estimated. Such estimations are often performed manually by experts who possess information about the environment and are familiar with the capabilities of the robotic system or using simplified experiments. In this paper, we present an automated pipeline for generating traversability costs that use recorded locomotion data from a realistic experiment and descriptive information on the terrain obtained from earth observation data. The main contribution is that the cost estimation for different terrain types is based on locomotion data obtained in realistic standardized experiments. Moreover, by repeating the experiments with different robot systems we are easily able to reflect the actual capabilities of the 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 https://robonav.ist.tugraz.at/data/ • Pipeline to estimate traversability costs for robots using recorded locomotion data. • Interpolation of costs for uncovered terrain classes using order relations. • Realistic off-road locomotion datasets for four heterogeneous robots. • Provision of guidelines for robot-specific recording of locomotion data. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09218890
Volume :
168
Database :
Academic Search Index
Journal :
Robotics & Autonomous Systems
Publication Type :
Academic Journal
Accession number :
171828673
Full Text :
https://doi.org/10.1016/j.robot.2023.104494