RoboEarth Action Recipe Execution. - Daniel Di Marco; Moritz Tenorth; Kai Häussermann; Oliver Zweigle; Paul Levi (IAS (1), 2012)

Creating and using RoboEarth object models. - Daniel Di Marco; Andreas Koch 003; Oliver Zweigle; Kai Häussermann; Björn Schiessle; Paul Levi; Dorian Gálvez-López; Luis Riazuelo; Javier Civera 001; J. M. M. Montiel; Moritz Tenorth; Alexander Clifford Perzylo; et al. (ICRA, 2012)

Integrating planning and execution for ROS enabled service robots using hierarchical action representations. - Rob Janssen; Erik van Meijl; Daniel Di Marco; René van de Molengraft; Maarten Steinbuch (ICAR, 2013)

RoboEarth Action Recipe Execution. - Daniel Di Marco; Moritz Tenorth; Kai Häussermann; Oliver Zweigle; Paul Levi (Frontiers of Intelligent Autonomous Systems, 2013)

RoboEarth Semantic Mapping: A Cloud Enabled Knowledge-Based Approach. - Luis Riazuelo; Moritz Tenorth; Daniel Di Marco; Marta Salas; Dorian Gálvez-López; Lorenz Mösenlechner; Lars Kunze; Michael Beetz; Juan D. Tardós; Luis Montano; José María Martínez Montiel (IEEE Trans Autom. Sci. Eng., 2015)

Task execution on heterogeneous robot platforms. - Daniel Di Marco (Shaker Verlag, 2015)

Weed Management of the Future. - Sandra Amend; David Brandt; Daniel Di Marco; Tobias Dipper; Gabriel Gässler; Markus Höferlin; Maurice Gohlke; Katharina Kesenheimer; Peter Lindner 002; Roland Leidenfrost; Andreas Michaels; Tobias Mugele; et al. (Künstliche Intell., 2019)

Cognitive Weeding: An Approach to Single-Plant Specific Weed Regulation. - Mark Niemeyer; Marian Renz; Maren Pukrop; David Hagemann; Tim Zurheide; Daniel Di Marco; Markus Höferlin; Philipp Stark; Florian Rahe; Matthias Igelbrink; Mario Jenz; Thomas Jarmer 001; et al. (Künstliche Intell., 2023)