AI-Supported Collaborative Control and Trajectory Generation of Mobile Manipulators for Indoor Construction Tasks

Research Project 26-1 (RP 26-1)

Weiße Schrift


For the automation of indoor construction tasks specifically in existing buildings, mobile robots offer great flexibility and provide digital support for time-consuming tasks such as the positioning of building elements. In this research project, we focus on collaborative path and trajectory generation for a heterogeneous group of collaborating mobile robots equipped with sensors and different manipulator arms. The mobile manipulators can perform positioning tasks autonomously and with high precision. In order to optimize the construction with respect to execution time and accuracy, optimization-based and AI-supported methods for decentralized path and trajectory generation are investigated to enable real-time capability and to allow an adaptive replanning of trajectories based on sensor feedback and environmental maps. Therefore, indoor positioning and environmental sensing algorithms have to be developed using e.g. total stations, laser scanners, cameras, and IMUs. We will use the capability of simultaneous localization and mapping (SLAM) algorithms both for positioning of the mobile manipulators and the acquisition of 3D information of the respective indoor environment. The main goal will be the modification and development of highly precise SLAM approaches for real-time positioning and data collection for a digital twin of the construction site. This digital twin consists of an up-to-date semantically enriched consistent 3D model as represented by a labeled 3D point cloud or 3D voxel grid. 



Prof. Dr.-Ing. Dr. h.c. Oliver Sawodny
Institute for System Dynamics (ISYS), University of Stuttgart
Prof. Dr.-Ing. habil. Volker Schwieger
Institute of Engineering Geodesy (IIGS), University of Stuttgart
Prof. Dr.-Ing. Uwe Sörgel
Institute for Photogrammetry (IFP), University of Stuttgart


Dr.-Ing. Li Zhang (IIGS)  
apl. Prof. Dr.-Ing. Norbert Haala (IFP)
Sahar Abolhasani (IIGS)
Alice Hierholz (ISYS)
Lena Joachim (IFP)
Vincent Reß (IFP)



  1. 2024

    1. Gienger, A., Stein, C., Lauer, A. P. R., Sawodny, O., & Tarín, C. (2024). Data-Based Reachability Analysis and Optimized Robot Positioning for Co-Design of Construction Processes. 2024 IEEE/SICE International Symposium on System Integration (SII).
  2. 2023

    1. Koelle, M., Walter, V., Schmohl, S., & Soergel, U. (2023). LEARNING ON THE EDGE: BENCHMARKING ACTIVE LEARNING FOR THE SEMANTIC SEGMENTATION OF ALS POINT CLOUDS. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, X-1/W1-2023, 945--952.
    2. Hierholz, A., Gienger, A., & Sawodny, O. (2023). Cooperative Time-Optimal Trajectory Generation for a Heterogeneous Group of Redundant Mobile Manipulators. Proceedings of the 2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 1296–1301.
    3. Haala, N., Zhang, W., Joachim, L., Skuddis, D., Abolhasani, S., Schwieger, V., & Soergel, U. (2023). Zum Potenzial von SLAM-Verfahren für geodätische Echtzeit-Messaufgaben. Allgemeine Vermessungsnachrichten (Avn), 163–172.
    4. Haala, N., Zhang, W., Joachim, L., & Skuddis, D. (2023). SLAM für die Echtzeit-Erfassung von Innenräumen. 22. Internationale Geodätische Woche Obergurgl 2022, 188–179.
    5. Christos Parlapanis, Matthias Frontull, Oliver Sawodny. (2023). Feed-Forward Control of a Construction Vehicle’s Hydro-Mechanical Powertrain to Prevent Engine Stalling. Proceedings of the 2023 IEEE Conference on Systems, Man, and Cybernetics (SMC).



      To the top of the page