@InProceedings{Eichenbaum-etAl_CASE2023_Towards-Lifelong-Mapping,
  author       = {Eichenbaum, Julian and Nikolovski, Gjorgji and M{\"u}lhens, Leon
                  and Reke, Michael and Ferrein, Alexander and Scholl, Ingrid},
  title        = {Towards a Lifelong Mapping Approach Using Lanelet 2 for Autonomous Open-Pit Mine Operations}, 
  booktitle    = {19th IEEE International Conference on Automation Science and Engineering (CASE)}, 
  year         = {2023},
  month        = {Aug},
  day          = {26-30},
  location     = {Auckland, New Zealand},
  pages        = {1--8},
  doi          = {10.1109/CASE56687.2023.10260526},
  url_ieeexpl  = {https://ieeexplore.ieee.org/abstract/document/10260526},
  ISSN         = {2161-8089},
  keywords     = {Geometry;Shape;Navigation;Roads;Operating systems;Semantics;Object detection},
  abstract     = {Autonomous agents require rich environment models
                  for fulfilling their missions. High-definition maps
                  are a well-established map format which allows for
                  representing semantic information besides the usual
                  geometric information of the environment. These are,
                  for instance, road shapes, road markings, traffic
                  signs or barriers. The geometric resolution of HD
                  maps can be as precise as of centimetre level. In
                  this paper, we report on our approach of using HD
                  maps as a map representation for autonomous
                  load-haul-dump vehicles in open-pit mining
                  operations. As the mine undergoes constant change,
                  we also need to constantly update the
                  map. Therefore, we follow a lifelong mapping
                  approach for updating the HD maps based on
                  camera-based object detection and GPS data. We show
                  our mapping algorithm based on the Lanelet 2 map
                  format and show our integration with the navigation
                  stack of the Robot Operating System. We present
                  experimental results on our lifelong mapping
                  approach from a real open-pit mine.},
}

{"_id":"heaZYx7doT67DXwN2","bibbaseid":"eichenbaum-nikolovski-mlhens-reke-ferrein-scholl-towardsalifelongmappingapproachusinglanelet2forautonomousopenpitmineoperations-2023","author_short":["Eichenbaum, J.","Nikolovski, G.","Mülhens, L.","Reke, M.","Ferrein, A.","Scholl, I."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"propositions":[],"lastnames":["Eichenbaum"],"firstnames":["Julian"],"suffixes":[]},{"propositions":[],"lastnames":["Nikolovski"],"firstnames":["Gjorgji"],"suffixes":[]},{"propositions":[],"lastnames":["Mülhens"],"firstnames":["Leon"],"suffixes":[]},{"propositions":[],"lastnames":["Reke"],"firstnames":["Michael"],"suffixes":[]},{"propositions":[],"lastnames":["Ferrein"],"firstnames":["Alexander"],"suffixes":[]},{"propositions":[],"lastnames":["Scholl"],"firstnames":["Ingrid"],"suffixes":[]}],"title":"Towards a Lifelong Mapping Approach Using Lanelet 2 for Autonomous Open-Pit Mine Operations","booktitle":"19th IEEE International Conference on Automation Science and Engineering (CASE)","year":"2023","month":"Aug","day":"26-30","location":"Auckland, New Zealand","pages":"1–8","doi":"10.1109/CASE56687.2023.10260526","url_ieeexpl":"https://ieeexplore.ieee.org/abstract/document/10260526","issn":"2161-8089","keywords":"Geometry;Shape;Navigation;Roads;Operating systems;Semantics;Object detection","abstract":"Autonomous agents require rich environment models for fulfilling their missions. High-definition maps are a well-established map format which allows for representing semantic information besides the usual geometric information of the environment. These are, for instance, road shapes, road markings, traffic signs or barriers. The geometric resolution of HD maps can be as precise as of centimetre level. In this paper, we report on our approach of using HD maps as a map representation for autonomous load-haul-dump vehicles in open-pit mining operations. As the mine undergoes constant change, we also need to constantly update the map. Therefore, we follow a lifelong mapping approach for updating the HD maps based on camera-based object detection and GPS data. We show our mapping algorithm based on the Lanelet 2 map format and show our integration with the navigation stack of the Robot Operating System. We present experimental results on our lifelong mapping approach from a real open-pit mine.","bibtex":"@InProceedings{Eichenbaum-etAl_CASE2023_Towards-Lifelong-Mapping,\n author = {Eichenbaum, Julian and Nikolovski, Gjorgji and M{\\\"u}lhens, Leon\n and Reke, Michael and Ferrein, Alexander and Scholl, Ingrid},\n title = {Towards a Lifelong Mapping Approach Using Lanelet 2 for Autonomous Open-Pit Mine Operations}, \n booktitle = {19th IEEE International Conference on Automation Science and Engineering (CASE)}, \n year = {2023},\n month = {Aug},\n day = {26-30},\n location = {Auckland, New Zealand},\n pages = {1--8},\n doi = {10.1109/CASE56687.2023.10260526},\n url_ieeexpl = {https://ieeexplore.ieee.org/abstract/document/10260526},\n ISSN = {2161-8089},\n keywords = {Geometry;Shape;Navigation;Roads;Operating systems;Semantics;Object detection},\n abstract = {Autonomous agents require rich environment models\n for fulfilling their missions. High-definition maps\n are a well-established map format which allows for\n representing semantic information besides the usual\n geometric information of the environment. These are,\n for instance, road shapes, road markings, traffic\n signs or barriers. The geometric resolution of HD\n maps can be as precise as of centimetre level. In\n this paper, we report on our approach of using HD\n maps as a map representation for autonomous\n load-haul-dump vehicles in open-pit mining\n operations. As the mine undergoes constant change,\n we also need to constantly update the\n map. Therefore, we follow a lifelong mapping\n approach for updating the HD maps based on\n camera-based object detection and GPS data. We show\n our mapping algorithm based on the Lanelet 2 map\n format and show our integration with the navigation\n stack of the Robot Operating System. We present\n experimental results on our lifelong mapping\n approach from a real open-pit mine.},\n}\n","author_short":["Eichenbaum, J.","Nikolovski, G.","Mülhens, L.","Reke, M.","Ferrein, A.","Scholl, I."],"key":"Eichenbaum-etAl_CASE2023_Towards-Lifelong-Mapping","id":"Eichenbaum-etAl_CASE2023_Towards-Lifelong-Mapping","bibbaseid":"eichenbaum-nikolovski-mlhens-reke-ferrein-scholl-towardsalifelongmappingapproachusinglanelet2forautonomousopenpitmineoperations-2023","role":"author","urls":{" ieeexpl":"https://ieeexplore.ieee.org/abstract/document/10260526"},"keyword":["Geometry;Shape;Navigation;Roads;Operating systems;Semantics;Object detection"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"http://maskor.fh-aachen.de/biblio/MASKOR.bib","dataSources":["i8ftsMK5wMbiNqmtB","pBDNm3knLemYTNMHw"],"keywords":["geometry;shape;navigation;roads;operating systems;semantics;object detection"],"search_terms":["towards","lifelong","mapping","approach","using","lanelet","autonomous","open","pit","mine","operations","eichenbaum","nikolovski","mülhens","reke","ferrein","scholl"],"title":"Towards a Lifelong Mapping Approach Using Lanelet 2 for Autonomous Open-Pit Mine Operations","year":2023}