Building and Navigation Strategies for On-Site Robotics

Research Project 17-1 (RP 17-1)

IntCDC Research Project 17-1 – Building and Navigation Strategies for On-Site Robotics
BUILDING AND NAVIGATION STRATEGIES FOR ON-SITE ROBOTIC CONSTRUCTION

Building construction typically relies on a centralized design, in which information is used to produce the most appropriate sequence of assembly actions which are assumed to serve as the unambiguous blueprint for building execution. However, uncertainties in actions which lead to violations of tolerances, true dimensions of fabricated modules as well as changes in the environment can require frequent replanning, the cost of which may be prohibitive for construction projects which have reached a level of complexity that becomes increasingly difficult to plan. For similar reasons on-site assembly is often prawn to purely reactive and manual operating sequences.

The central goal of this research project is to master the increasing level of complexity for on-site construction of high-performance building systems by decentralized planning strategies which compute smart assembly sequences based on AI reasoning and thus enable new processes in the research area of on-site large-scale robotic construction. This research project contributes significantly to the research network and demonstrator as it is the only project within the cluster with a focus on high-level planning for building execution.

 

PRINCIPAL INVESTIGATORS

Prof. Dr. rer. nat. Marc Toussaint
Machine Learning and Robotics Lab (IPVS-MLR), University of Stuttgart
Prof. Dr.-Ing. Dr. h.c. Oliver Sawodny
Institute for System Dynamics (ISYS), University of Stuttgart

TEAM

Dr.-Ing. Salih Özgür Ögüz
Theresa Baumann (ISYS)
Valentin Noah Hartmann (IPVS-MLR)

 

PEER-REVIEWED PUBLICATIONS

  1. 2022

    1. Grothe, F., Hartmann, V. N., Orthey, A., & Toussaint, M. (2022). ST-RRT*: Asymptotically-Optimal Bidirectional Motion Planning through Space-Time. Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA).
    2. Hartmann, V. N., Strub, M. P., Toussaint, M., & Gammell, J. D. (2022). Effort Informed Roadmaps (EIRM*): Efficient asymptotically optimal multiquery planning by actively reusing validation effort. Proceedings of the International Symposium on Robotics Research (ISRR). https://doi.org/10.1007/978-3-031-25555-7_37
    3. Hartmann, V. N., Orthey, A., Driess, D., Oguz, O. S., & Toussaint, M. (2022). Long-Horizon Multi-Robot Rearrangement Planning for Construction Assembly. IEEE Transactions on Robotics, 1–14. https://doi.org/10.1109/TRO.2022.3198020

  2. 2021

    1. Ortiz-Haro, J., Hartmann, V. N., Oguz, O. S., & Toussaint, M. (2021). Learning Efficient Constraint Graph Sampling for Robotic Sequential Manipulation. 2021 IEEE International Conference on Robotics and Automation (ICRA), 4606–4612. https://doi.org/10.1109/ICRA48506.2021.9560978
    2. Thomas, M., Qiu, J., & Sawodny, O. (2021). Trajectory sequence generation and static obstacle avoidance for automatic positioning tasks with a tower crane. Proceedings of the 47th Annual Conference of the IEEE IES (IECON).

  3. 2020

    1. Hartmann, V. N., Oguz, O. S., & Toussaint, M. (2020). Planning Planning: The Path Planner as a Finite State Machine. Workshop on Planning and Robotics (PlanRob).
    2. Hartmann, V. N., Oguz, O. S., Driess, D., Toussaint, M., & Menges, A. (2020). Robust Task and Motion Planning for Long-Horizon Architectural Construction Planning. Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS).

OTHER PUBLICATIONS

  1. 2023

    1. Hartmann, V. N., & Toussaint, M. (2023). Towards computing low-makespan solutions for multi-arm multi-task planning problems. https://doi.org/10.48550/arXiv.2305.17527

DATA SETS

        

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