TY - GEN
T1 - Terrain segmentation for commercial vehicles and working machines
AU - Edlinger, Raimund
AU - Mitterhuber, Ulrich
AU - Nüchter, Andreas
N1 - Funding Information:
The research of these results has been accomplished within the SMARTER - Slope Maintenance Automation using Real-Time Telecommunication and advanced Environment Recognition project. This work has been funded by the Austrian Research Promotion Agency (FFG) within the program "Mobility of the future" No. 879646.
Publisher Copyright:
© 2023, Society for Imaging Science and Technology.
PY - 2023/1/16
Y1 - 2023/1/16
N2 - In the field of automated working machines, not only is the general trend towards automation in industry, transport and logistics reflected, but new areas of application and markets are also constantly emerging. In this paper we present a pipeline for terrain classification in off-road environments and in the field of "automated maintenance of slopes", which offers potential for solving numerous socioeconomic needs. Working tasks can be made more efficient, more ergonomic and, in particular, much safer, because mature, automated vehicles are used. At present, however, such tasks can only be carried out remotely or semi-automatically, under the supervision of a trained specialist. This only partially facilitates the work. The real benefit only comes when the supervising person is released from this task and is able to pursue other work. In addition to the development of a safe integrated system and sensor concept for use in public spaces as a basic prerequisite for vehicles licensed in the future, increased situational awareness of mobile systems through machine learning in order to increase their efficiency and flexibility, is also of great importance.
AB - In the field of automated working machines, not only is the general trend towards automation in industry, transport and logistics reflected, but new areas of application and markets are also constantly emerging. In this paper we present a pipeline for terrain classification in off-road environments and in the field of "automated maintenance of slopes", which offers potential for solving numerous socioeconomic needs. Working tasks can be made more efficient, more ergonomic and, in particular, much safer, because mature, automated vehicles are used. At present, however, such tasks can only be carried out remotely or semi-automatically, under the supervision of a trained specialist. This only partially facilitates the work. The real benefit only comes when the supervising person is released from this task and is able to pursue other work. In addition to the development of a safe integrated system and sensor concept for use in public spaces as a basic prerequisite for vehicles licensed in the future, increased situational awareness of mobile systems through machine learning in order to increase their efficiency and flexibility, is also of great importance.
UR - http://www.scopus.com/inward/record.url?scp=85169578220&partnerID=8YFLogxK
U2 - 10.2352/EI.2023.35.5.IRIACV-324
DO - 10.2352/EI.2023.35.5.IRIACV-324
M3 - Conference contribution
VL - 35
T3 - IS and T International Symposium on Electronic Imaging Science and Technology
SP - 1
EP - 7
BT - Electronic Imaging
PB - Society for Imaging Science and Technology
CY - IS&T 7003 Kilworth Lane, Springfield, VA 22151 USA
ER -