Robotics
Robotics deals in general with machines that can assist in or perform the execution of tasks such as assembly or machining by industrial robots. Research projects in this area concern, for example, the control of motions and forces in human-robot interaction as well as the planning of paths and trajectories for mobile and collaborative robots.
Contact
Dr.-Ing. Andreas Völz
Tel.: +49 9131 85-61036
E-Mail | Homepage
Prof. Dr.-Ing. Knut Graichen
Tel.: +49 9131 85-27127
E-Mail | Homepage
Robots should move and interact with humans as efficiently as possible. If this includes high velocities or heavy payloads, the nonlinear rigid body dynamics as well as the input constraints need to be taken into account, which leads to a computationally demanding optimization problem. On the other hand, when the robot is in contact with its environment, the rigid body dynamics are often less relevant, but the forces and torques that arise must be considered by the control system. This is especially important for safe human-robot interaction. Here, the challenges include the contact modelling (e.g. stiffness and friction), the safe handling of contact loss, or the selection of controller parameters for different applications. Current research considers model predictive interaction control (MPIC), which refers to MPC with explicit prediction of contact forces and torques, as well as the development of specialized algorithms for solving optimization problems with rigid body dynamics.
Besides controlling motions, also the planning of paths (geometric description) and trajectories (time information) is a relevant problem for many types of robots. In particular for mobile and collaborative robots, motions should be planned in such a way that they do not cause self-collisions or collisions with obstacles in the environment. Global planners iteratively build a search structure that explores the space of possible motions, whereas local planners only search in the neighborhood of an initial solution. In order to efficiently find high-quality solutions, it is necessary to combine the advantages of both global and local planning methods. Further difficulties arise in dynamic environments, where the future motion of obstacles needs to be predicted or for car-like robots, where the non-holonomic kinematics need to be considered.
The Chair is equipped with a mobile dual-arm robot as well as a motion capturing system that have been funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) through the major instrumentation proposal INST 90/1167-1 FUGG. The system enables the experimental validation of planning and control methods for mobile manipulation in workspaces shared with humans. For more information contact Prof. Dr.-Ing. Knut Graichen or Dr.-Ing. Andreas Völz.
Videos
Robot-environment interaction control
- Writing on a blackboard with chalk – MPIC hybrid force/motion control (IEEE IROS 2020: DOI: 10.1109/IROS45743.2020.9341168)
- Anthropomorphic in-hand manipulation – MPIC for force closure grasping (IEEE CDC 2021)
- Catching objects in flight – MPIC for time-optimal trajectory planning
- Admittance control of the XPlanar system for human-mover interaction
Collision-free motion planning
- Collision-free motion planning for a rotating robot with seven degrees of freedom
- Collision-free motion planning for a dual-arm robot with twelve degrees of freedom
- Motion planning for a dual-arm robot with closed kinematics
- Predictive path-following control for continuous replanning with dynamic roadmaps (IEEE RA-L 2019, DOI: 1109/LRA.2019.2929990)
Related projects since 2021
Cooperative manipulation with dual-arm robots at the payload limit
Dual-armrobots offer a high potential for automation technology, as they canbe used to implement tasks that are not possible with one arm alone.This includes in particular the manipulation of large or heavyobjects that exceed the payload of a single arm. Illustrativeexamples are the movement of beverage crates, long boards or pipes,which are also preferably grasped by humans with both hands.
However,cooperative manipulation is particularly challenging, because botharms…
Kinesthetic teaching and predictive control of interaction tasks in robotics
Precise interactions as part of industrial manufacturing tasks are typically very complex to characterize and implement. One reason for this is the heterogeneity of the task-specific requirements for the motion and control behavior. A direct implementation of the task into a robot program therefore requires highly qualified specialists and is only profitable for large lot sizes. For a flexible applicability and easy (re-)configuration of the robot system, an approach to programming by kinesthetic…
Motion planning for driving simulators
KARMA: Development of an innovative camera-based framework for collision-free human-machine movement
Receding horizon time-optimal path parameterization for robotic manipulators
AMOR: Advanced monitoring and optimization for robotic strain wave gears
Related publications
Since 2022
- Snobar, F., Reinhard, J., Huber, H., Hoffmann, M., Stelzig, M., Vossiek, M., & Graichen, K. (2022). FOV-based model predictive object tracking for quadcopters. In Proceedings of the 9th IFAC Symposium on Mechatronic Systems (Mechatronics 2022) (pp. 13 - 18). Los Angeles, CA (USA).
- Dio, M., Völz, A., & Graichen, K. (2023). Cooperative dual-arm control for heavy object manipulation based on hierarchical quadratic programming. In Proceedings of the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 643-648). Detroit, US.
- Snobar, F., Reinhard, J., Huber, H., Hoffmann, M., Stelzig, M., Vossiek, M., & Graichen, K. (2022). FOV-based model predictive object tracking for quadcopters. In Proceedings of the 9th IFAC Symposium on Mechatronic Systems (Mechatronics 2022) (pp. 13 - 18). Los Angeles, CA (USA).
- Dio, M., Völz, A., & Graichen, K. (2023). Cooperative dual-arm control for heavy object manipulation based on hierarchical quadratic programming. In Proceedings of the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 643-648). Detroit, US.
2021
- Burk, D., Völz, A., & Graichen, K. (2021). Experimental validation of the open-source DMPC framework GRAMPC-D applied to the remote-accessible robotarium. In Proceedings of the IEEE International Conference on Mechatronics and Automation (ICMA).
- Völz, A., & Graichen, K. (2021). Gradient-based nonlinear model predictive control for systems with state-dependent mass matrix. In Proceedings of the 2021 IEEE Conference on Decision and Control (CDC), accepted.
- Burk, D., Völz, A., & Graichen, K. (2021). Experimental validation of the open-source DMPC framework GRAMPC-D applied to the remote-accessible robotarium. In Proceedings of the IEEE International Conference on Mechatronics and Automation (ICMA).
- Völz, A., & Graichen, K. (2021). Gradient-based nonlinear model predictive control for systems with state-dependent mass matrix. In Proceedings of the 2021 IEEE Conference on Decision and Control (CDC), accepted.
2020
- Graichen, K., & Völz, A. (2020). Prädiktive Pfadfolgeregelung für die kollisionsfreie Bewegungsplanung von Robotern.
- Völz, A., & Graichen, K. (2020). Prädiktive Pfadfolgeregelung für die kollisionsfreie Bewegungsplanung von Robotern. At-Automatisierungstechnik, 68(7), 557-570. https://doi.org/10.1515/auto-2020-0048
- Graichen, K., & Völz, A. (2020). Prädiktive Pfadfolgeregelung für die kollisionsfreie Bewegungsplanung von Robotern.
- Völz, A., & Graichen, K. (2020). Prädiktive Pfadfolgeregelung für die kollisionsfreie Bewegungsplanung von Robotern. At-Automatisierungstechnik, 68(7), 557-570. https://doi.org/10.1515/auto-2020-0048
2019
- Völz, A., & Graichen, K. (2019). A predictive path-following controller for continuous replanning with dynamic roadmaps. IEEE Robotics and Automation Letters, 4(4), 3963-3970. https://doi.org/10.1109/LRA.2019.2929990
- Völz, A., & Graichen, K. (2019). A predictive path-following controller for continuous replanning with dynamic roadmaps. IEEE Robotics and Automation Letters, 4(4), 3963-3970. https://doi.org/10.1109/LRA.2019.2929990
2018 and earlier
- Völz, A., & Graichen, K. (2018). An optimization-based approach to dual-arm motion planning with closed kinematics. In Proceedings 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 8346-8351). Madrid (Spain).
- Graichen, K., & Hentzelt, S. (2015). A bi-level nonlinear predictive control scheme for hopping robots with hip and tail actuation. In Proceedings 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2015) (pp. 4480-4485). Hamburg (Germany).
- Völz, A., & Graichen, K. (2017). Composition of dynamic roadmaps for dual-arm motion planning. In Proceedings 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM 2017) (pp. 1242-1248). Munich (Germany).
- Völz, A., & Graichen, K. (2018). Computation of collision distance and gradient using an automatic sphere approximation of the robot model with bounded error. In Proceedings 50th International Symposium on Robotics (ISR) (pp. 322-329). München (Germany).
- Völz, A., & Graichen, K. (2016). Distance metrics for path planning with dynamic roadmaps. In Proceedings 47th International Symposium on Robotics (ISR) (pp. 126-132). München (Germany).
- Völz, A., & Graichen, K. (2018). An optimization-based approach to dual-arm motion planning with closed kinematics. In Proceedings 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 8346-8351). Madrid (Spain).
- Graichen, K., & Hentzelt, S. (2015). A bi-level nonlinear predictive control scheme for hopping robots with hip and tail actuation. In Proceedings 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2015) (pp. 4480-4485). Hamburg (Germany).
- Völz, A., & Graichen, K. (2017). Composition of dynamic roadmaps for dual-arm motion planning. In Proceedings 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM 2017) (pp. 1242-1248). Munich (Germany).
- Völz, A., & Graichen, K. (2018). Computation of collision distance and gradient using an automatic sphere approximation of the robot model with bounded error. In Proceedings 50th International Symposium on Robotics (ISR) (pp. 322-329). München (Germany).
- Völz, A., & Graichen, K. (2016). Distance metrics for path planning with dynamic roadmaps. In Proceedings 47th International Symposium on Robotics (ISR) (pp. 126-132). München (Germany).