@InProceedings{ Ferrein-etAl_ICAART2023_Towards-a-Fleet,
  author       = {Alexander Ferrein and Michael Reke and Ingrid Scholl and Benjamin Decker
                  and Nicolas Limpert and Gjorgji Nikolovski and Stefan Schiffer},
  title        = {Towards a Fleet of Autonomous Haul-Dump Vehicles in Hybrid Mines},
  booktitle    = {Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
  year         = {2023},
  pages        = {278--288},
  publisher    = {SciTePress},
  organization = {INSTICC},
  doi          = {10.5220/0011693600003393},
  url_sciteprs = {https://www.scitepress.org/Papers/2023/116936/},
  url_PDF      = {https://www.scitepress.org/Papers/2023/116936/116936.pdf},
  isbn         = {978-989-758-623-1},
  abstract     = {Like many industries, the mining industry is facing
                  major transformations towards more sustainable and
                  decarbonised operations with smaller environmental
                  footprints. Even though the mining industry, in
                  general, is quite conservative, key drivers for
                  future developments are digitalisation and
                  automation. Another direction forward is to mine
                  deeper and reduce the mine footprint at the
                  surface. This leads to so-called hybrid mines, where
                  part of the operation is open pit, and part of the
                  mining takes place underground. In this paper, we
                  present our approach to running a fleet of
                  autonomous hauling vehicles suitable for hybrid
                  mining operations. We present a ROS 2-based
                  architecture for running the vehicles. The fleet of
                  currently three vehicles is controlled by a
                  SHOP3-based planner which dispatches missions to the
                  vehicles. The basic actions of the vehicles are
                  realised as behaviour trees in ROS 2. We used a deep
                  learning network for detection and classification of
                  mining objects trained with a mixing of synthetic
                  and real world training images. In a life-long
                  mapping approach, we define lanelets and show their
                  integration into HD maps. We demonstrate a
                  proof-of-concept of the vehicles in operation in
                  simulation and in real-world experiments in a gravel
                  pit.},
}
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%  2022
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

{"_id":"7wmxgNsrpu6JvcszD","bibbaseid":"ferrein-reke-scholl-decker-limpert-nikolovski-schiffer-towardsafleetofautonomoushauldumpvehiclesinhybridmines-2023","author_short":["Ferrein, A.","Reke, M.","Scholl, I.","Decker, B.","Limpert, N.","Nikolovski, G.","Schiffer, S."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["Alexander"],"propositions":[],"lastnames":["Ferrein"],"suffixes":[]},{"firstnames":["Michael"],"propositions":[],"lastnames":["Reke"],"suffixes":[]},{"firstnames":["Ingrid"],"propositions":[],"lastnames":["Scholl"],"suffixes":[]},{"firstnames":["Benjamin"],"propositions":[],"lastnames":["Decker"],"suffixes":[]},{"firstnames":["Nicolas"],"propositions":[],"lastnames":["Limpert"],"suffixes":[]},{"firstnames":["Gjorgji"],"propositions":[],"lastnames":["Nikolovski"],"suffixes":[]},{"firstnames":["Stefan"],"propositions":[],"lastnames":["Schiffer"],"suffixes":[]}],"title":"Towards a Fleet of Autonomous Haul-Dump Vehicles in Hybrid Mines","booktitle":"Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART","year":"2023","pages":"278–288","publisher":"SciTePress","organization":"INSTICC","doi":"10.5220/0011693600003393","url_sciteprs":"https://www.scitepress.org/Papers/2023/116936/","url_pdf":"https://www.scitepress.org/Papers/2023/116936/116936.pdf","isbn":"978-989-758-623-1","abstract":"Like many industries, the mining industry is facing major transformations towards more sustainable and decarbonised operations with smaller environmental footprints. Even though the mining industry, in general, is quite conservative, key drivers for future developments are digitalisation and automation. Another direction forward is to mine deeper and reduce the mine footprint at the surface. This leads to so-called hybrid mines, where part of the operation is open pit, and part of the mining takes place underground. In this paper, we present our approach to running a fleet of autonomous hauling vehicles suitable for hybrid mining operations. We present a ROS 2-based architecture for running the vehicles. The fleet of currently three vehicles is controlled by a SHOP3-based planner which dispatches missions to the vehicles. The basic actions of the vehicles are realised as behaviour trees in ROS 2. We used a deep learning network for detection and classification of mining objects trained with a mixing of synthetic and real world training images. In a life-long mapping approach, we define lanelets and show their integration into HD maps. We demonstrate a proof-of-concept of the vehicles in operation in simulation and in real-world experiments in a gravel pit.","bibtex":"@InProceedings{ Ferrein-etAl_ICAART2023_Towards-a-Fleet,\n author = {Alexander Ferrein and Michael Reke and Ingrid Scholl and Benjamin Decker\n and Nicolas Limpert and Gjorgji Nikolovski and Stefan Schiffer},\n title = {Towards a Fleet of Autonomous Haul-Dump Vehicles in Hybrid Mines},\n booktitle = {Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},\n year = {2023},\n pages = {278--288},\n publisher = {SciTePress},\n organization = {INSTICC},\n doi = {10.5220/0011693600003393},\n url_sciteprs = {https://www.scitepress.org/Papers/2023/116936/},\n url_PDF = {https://www.scitepress.org/Papers/2023/116936/116936.pdf},\n isbn = {978-989-758-623-1},\n abstract = {Like many industries, the mining industry is facing\n major transformations towards more sustainable and\n decarbonised operations with smaller environmental\n footprints. Even though the mining industry, in\n general, is quite conservative, key drivers for\n future developments are digitalisation and\n automation. Another direction forward is to mine\n deeper and reduce the mine footprint at the\n surface. This leads to so-called hybrid mines, where\n part of the operation is open pit, and part of the\n mining takes place underground. In this paper, we\n present our approach to running a fleet of\n autonomous hauling vehicles suitable for hybrid\n mining operations. We present a ROS 2-based\n architecture for running the vehicles. The fleet of\n currently three vehicles is controlled by a\n SHOP3-based planner which dispatches missions to the\n vehicles. The basic actions of the vehicles are\n realised as behaviour trees in ROS 2. We used a deep\n learning network for detection and classification of\n mining objects trained with a mixing of synthetic\n and real world training images. In a life-long\n mapping approach, we define lanelets and show their\n integration into HD maps. We demonstrate a\n proof-of-concept of the vehicles in operation in\n simulation and in real-world experiments in a gravel\n pit.},\n}\n% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n% 2022\n% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n\n","author_short":["Ferrein, A.","Reke, M.","Scholl, I.","Decker, B.","Limpert, N.","Nikolovski, G.","Schiffer, S."],"key":"Ferrein-etAl_ICAART2023_Towards-a-Fleet","id":"Ferrein-etAl_ICAART2023_Towards-a-Fleet","bibbaseid":"ferrein-reke-scholl-decker-limpert-nikolovski-schiffer-towardsafleetofautonomoushauldumpvehiclesinhybridmines-2023","role":"author","urls":{" sciteprs":"https://www.scitepress.org/Papers/2023/116936/"," pdf":"https://www.scitepress.org/Papers/2023/116936/116936.pdf"},"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"http://maskor.fh-aachen.de/biblio/MASKOR.bib","dataSources":["i8ftsMK5wMbiNqmtB","pBDNm3knLemYTNMHw"],"keywords":[],"search_terms":["towards","fleet","autonomous","haul","dump","vehicles","hybrid","mines","ferrein","reke","scholl","decker","limpert","nikolovski","schiffer"],"title":"Towards a Fleet of Autonomous Haul-Dump Vehicles in Hybrid Mines","year":2023}