Zugehörige Institution(en) am KIT | Institut für Anthropomatik und Robotik (IAR) |
Publikationstyp | Hochschulschrift |
Publikationsjahr | 2020 |
Sprache | Englisch |
Identifikator | KITopen-ID: 1000104500 |
Verlag | Karlsruher Institut für Technologie (KIT) |
Umfang | X, 210 S. |
Art der Arbeit | Dissertation |
Fakultät | Fakultät für Informatik (INFORMATIK) |
Institut | Institut für Anthropomatik und Robotik (IAR) |
Prüfungsdatum | 11.12.2019 |
Bemerkung zur Veröffentlichung | In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of KIT's products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink. |
Schlagwörter | automated driving, nonholonomic motion planning, belief space planning, collision avoidance, probabilistic collision checking, deep learning in robotics |
Referent/Betreuer | Zöllner, J. M. |