Flexible Interaction for infrastructures establishment by means of teleoperation and direct collaboration; transfer into industry 4.0

The project TransFIT is part of the space road map of the DFKI RIC. The project focuses on the assembly and installation of infrastructure for space applications by humans and robots either autonomously or in cooperation. The cooperation between humans and robots follows the concept of “sliding autonomy”. This means that the control over a robot by a human can be very strong as it is the case during teleoperation, weaker as in case of teleoperation with an autonomous control of components or like supervision only in case of “operator in the loop” approaches. The goal of the human-robot interaction is not only task sharing but further training of robots enabling more complex autonomous behaviour.

Duration: 01.07.2017 till 31.12.2021
Donee: German Research Center for Artificial Intelligence GmbH & Siemens AG & University of Bremen
Sponsor: Federal Ministry for Economic Affairs and Climate Action
German Aerospace Center e.V.
Grant number: FKZ 50RA1701, FKZ 50RA1702 und FKZ 50RA1703.
Application Field: Space Robotics
Related Projects: BesMan
Behaviors for Mobile Manipulation (05.2012- 07.2016)
Dual-arm exoskeleton (01.2011- 12.2013)
Intelligent Man-Machine Interface - Adaptive Brain-reading for assistive robotics (05.2010- 04.2015)
Intelligent Human-Robot Collaboration (03.2015- 06.2016)
Intelligent Structures for Mobile Robots (05.2010- 08.2013)
Learning Intelligent Motions for Kinematically Complex Robots for Exploration in Space (05.2012- 04.2016)
Technologies and Human-Robot Collaboration for Surface EVA Exploration Activities and Training in European Analogue Environments (09.2013- 08.2016)
Recupera REHA
Full-body exoskeleton for upper body robotic assistance (09.2014- 12.2017)
Semi-autonomous cooperative exploration of planetary surfaces including the installation of a logistic chain as well as consideration of the terrestrial applicability of individual aspects (05.2013- 12.2017)
Related Robots: Full Body Exoskeleton
Exoskeleton for upper body robotic assistance
Dual Arm Exoskeleton
Exoskeleton for upper body robotic assistance (Recupera REHA)
Related Software: Bagel
Biologically inspired Graph-Based Language
Signal Processing and Classification Environment written in Python
Reconfigurable Signal Processing and Classification Environment
Behavior Optimization and Learning for Robots
Robot Construction Kit

Project details

Requirements for the space application

Future space missions will not only include sending scientific equipment close to astronomical objects or even onto planets, moons or astroids using landers and robots, but will further include humans as an important part of the mission on-site. Therefore setting up local infrastructure like stationary camp sites, laboratories or even more complex and bigger module-based structures is required. To prevent unneccessary endangerment of the astronauts being on away missions the usage of robots is obvious. Since robots only have a limited capability of solving complex tasks and only have a limited flexibility in their behavior, a strong cooperation and collaboration with the astronaut is neccessary starting with a general objective for the (semi)-autonomous robots to a direct and intuitive robot control. Like this, the robot is on the one hand able to interact directly with the human, for example holding or fixing a module while the human is assembling a second module, on the other hand another astronaut can teleoperate the robot from the base camp or a space station in the orbit.

An important goal of TransFIT is the development of robot skills which enable the robot to complete complex assembly tasks like grabbing, holding and putting together prefabricated components autonomously or in collaboration with the human. Therefore, the concept of "sliding autonomy" as a dynamic change between fully autonomous behavior, semi-autonomous and cooperative behavior either with the operator in the loop or as a partner and teleoperation will be implemented. Hence, a simple control software is required for a fast adaptation of the behavior on-site and during a mission. 

Additionally, the robot should be able to learn new skills from interacting with the human to further optimize his versatility and adaptability to specific requirements. In the final scenario, two robots and at least one human will assemble infrastructure by autonomously putting together parts by the robot, putting together parts in cooperation with a human and also teleoperated by a human. Furthermore we will show that the robots behavior can be easily adapted by an interface to semi-autonomously create installation instructions and by learning skills from observing human behavior.

Transfer in the context of Industry 4.0

The demand for flexible automation is increasing rapidly. Main driver is the ongoing industrial revolution, especially in high wage countries like Germany. This revolution is characterized by constantly increasing numbers of product variants, constantly decreasing product life cycles and, as a consequence, constantly decreasing lot sizes. End-to-end automation using classic approaches is not always feasible in this context, leading to extremely low degrees of automation in large phases of production. One of the phases still executed mostly manually is discrete manufacturing. Automation, using classical approaches, is not cost-effective for large number of product variants due to the associated high engineering costs. New automation approaches need to be developed and tested. One of the main goals of the TransFit project is the transfer of technology developed for extraterrestrial applications into industrial assembly applications. In the project, a highly-flexible, universal and cooperative assembly cell for the manufacturing of complex components will be build for demonstrating this technology transfer.

To achieve the required universality and flexibility, without incurring in high engineering costs, future assembly cells have to be able to execute, autonomously, and in cooperation with the operator, abstract job specifications without the need of detailed programming. These are also requirements for the extraterrestrial assembly and installation of infrastructure. The solutions and interfaces developed in the extraterrestrial scenario should also be applicable in the industrial scenario, where devices with a maximal total weight of 10 kg are to be manufactured in collaboration with a human coworker. The job specification contains assembly steps that, due to the required dexterity can only be performed by the human, and also contains steps that the system can perform with greater precision and repeatability.

The assembly cell has a high degree of autonomy and does not rely on special-purpose tools or sensors. A system-independent semantic description of the process (Bill-of-Process) and product (Bill-of-Material) is given together with a semantic description of the assembly cell including its product-independent skills. The system relies on sensor data to determine its current situation. Using reasoning and planning based on the current situation and the explicit knowledge, the system is able to compute a sequence of actions for assembling a given product. These actions consist of a high-level representation of the capabilities or skills of the system. The system and the human coworker carry out the assembly task together. If one of the steps cannot be executed by the system, then the human is indicated what to do in order to carry out the step. 

In summary, the following objectives will be targeted in the project:

  • Development of hardware and software solutions for a safe human-machine cooperation using a demand-driven sliding autonomy.
  • Development of knowledge-based technologies for robot control and environment perception for the application of setting up an infrastructure.
  • Development of a semi-autonomous assistency system for an intuitive human-machine-interaction supporting the astronaut depending on his/her current situation and based on automated feedback approaches using psychophysiological data.
  • Increase of the autonomy of robots based on online-learning for behavior optimization, automatic adaptation to hardware changes and learning from interacting with the human ("operator in the loop" approach).
  • Transfer of the developed technologies into the context of industry 4.0 with the aim of an interactive and flexible assembly cell.


RH5 Manus: Introduction of a Powerful Humanoid Upper Body Design for Dynamic Movements

Recent studies suggest that a stiff structure along with an optimal mass distribution are key features to perform dynamic movements, and parallel designs provide these characteristics to a robot. This work presents the new upper-body design of the humanoid robot RH5 named RH5 Manus, with series-parallel hybrid design. The new design choices allow us to perform dynamic motions including tasks that involve a payload of 4 kg in each hand,

and fast boxing motions. The parallel kinematics combined with an overall serial chain of the robot provides us with high force production along with a larger range of motion and low peripheral inertia. The robot is equipped with force-torque sensors, stereo camera, laser scanners, high-resolution encoders etc that provide interaction with operators and environment. We generate several diverse dynamic motions using trajectory optimization, and successfully execute them on the robot with accurate trajectory and velocity tracking, while respecting joint rotation, velocity, and torque limits.

RH5 Manus: Humanoid assistance robot for future space missions

The humanoid robot "RH5 Manus" was developed as part of the "TransFIT" project as an assistance robot that can be used in the direct human environment, for example on a future moon station. The aim was to equip the robot with the necessary capabilities to perform complex assembly work autonomously, as well as in cooperation with astronauts and teleoperated. Another focus of the project was on the transfer of the developed technologies to industrial manufacturing and production. The video shows the mechanical assembly and the commissioning of the robot.

TransFIT: Flexible interaction for infrastructures establishment

Flexible interaction for infrastructures establishment by means of teleoperation and direct collaboration; transfer into industry 4.0.

Intrinsic interactive reinforcement learning: Using error-related potentials

Thanks to human negative feedback, the robot learns from its own misconduct.



Asynchronous classification of error-related potentials in human-robot interaction
Su-Kyoung Kim, Michael Maurus, Mathias Trampler, Marc Tabie, Elsa Andrea Kirchner
In 25th International Conference on Human-Computer Interaction, (HCII-2023), 23.7.-28.7.2023, Copenhagen, Springer, Jul/2023.
Detection and recognition of human manipulation building blocks
Lisa Gutzeit
Mar/2023. Universität Bremen.
Actuator-Level Motion and Contact Episode Learning and Classification Using Adaptive Resonance Theory
Vinzenz Bargsten, Frank Kirchner
In Journal of Intelligent Service Robotics, Springer, volume 1, pages 1-12, 2023.


Unsupervised Segmentation of Human Manipulation Movements into Building Blocks
Lisa Gutzeit, Frank Kirchner
In IEEE Access, IEEE, volume 10, pages 125723-125734, Dec/2022.
Hierarchical Segmentation of Human Manipulation Movements
Lisa Gutzeit
In Proc. of the 26th International Conference on Pattern Recognition, (ICPR-2022), 21.8.-25.8.2022, Montreal, QC, IEEE Computer Society, pages 2742-2748, Aug/2022.
Kinematic Analysis of a Novel Humanoid Wrist Parallel Mechanism
Christoph Stoeffler, Adriano del Rio Fernandez, Heiner Peters, Moritz Schilling, Shivesh Kumar
Editors: Bruno Siciliano, Oussama Khatib
In ARK 2022: Advances in Robot Kinematics 2022, (ARK-2022), 27.6.-30.6.2022, Bilbao, Springer, series Springer Proceedings in Advanced Robotics, volume 24, pages 348-355, Jun/2022. ISBN: 978-3-031-08140-8.
Learning Task Constraints for Whole-Body Control of Robotic Systems
Dennis Mronga
May/2022. Universität Bremen.
Whole-Body Control of Series-Parallel Hybrid Robots
Dennis Mronga, Shivesh Kumar, Frank Kirchner
In IEEE International Conference on Robotics and Automation (ICRA), (ICRA-2022), 23.5.-27.5.2022, Philadelphia, IEEE, pages 228-234, 2022.
Introducing RH5 Manus: A Powerful Humanoid Upper Body Design for Dynamic Movements
Melya Boukheddimi, Shivesh Kumar, Heiner Peters, Dennis Mronga, Rohan Budhiraja, Frank Kirchner
In IEEE International Conference on Robotics and Automation (ICRA), (ICRA-2022), 23.5.-27.5.2022, Philadelphia, IEEE, pages 01-07, 2022. ISBN: 978-1-7281-9681-7.


Learning initial trajectory using sequence-to-sequence approach to warm start an optimization-based motion planner
Sankaranarayanan Natarajan
In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, (IROS-2021), 27.9.-01.10.2021, Prague/Virtual, o.A., Sep/2021.
Learning context-adaptive task constraints for robotic manipulation
Dennis Mronga, Frank Kirchner
In Robotics and Autonomous Systems, Elsevier, volume 141, pages 103779-103779, Jul/2021.
VR-Based Interface Enabling Ad-Hoc Individualization of Information Layer Presentation
Luka Jacke, Michael Maurus, Elsa Andrea Kirchner
In HCI International 2021 - Late Breaking Posters, Springer International Publishing, pages 324-331, Jul/2021. ISBN: 978-3-030-90176-9.
gmr: Gaussian Mixture Regression
Alexander Fabisch
In Journal of Open Source Software, The Open Journal, Journal of Open Source Software, volume 6, number 62, pages 3054, Jun/2021.
Active Exploitation of Redundancies in Reconfigurable Multi-Robot Systems
Thomas M. Roehr
In IEEE Transactions on Robotics, IEEE, volume n.n., pages 1-17, Jun/2021.
A Comparison of Few-Shot Classification of Human Movement Trajectories
Lisa Gutzeit
In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, (ICPRAM-2021), 04.2.-06.2.2021, SciTePress, pages 243-250, Feb/2021. ISBN: 978-989-758-486-2.
Experience-Based Behavior Adaptation of Kinematically-Complex Robots
Alexander Dettmann
In n.n., Feb/2021. Universität Bremen.


Errors in human-robot interactions and their effects on robot learning
Su-Kyoung Kim, Elsa Andrea Kirchner, Lukas Schloßmüller, Frank Kirchner
In Frontiers in Robotics and AI, Frontiers, volume 7 - Section Computational Intelligence in Robotics, pages Article-558531, Oct/2020.
Flexible online adaptation of learning strategy using EEG-based reinforcement signals in real-world robotic applications
Su Kyoung Kim, Elsa Andrea Kirchner, Frank Kirchner
In Proceedings of the IEEE International Conference on Robotics and Automation, (ICRA-2020), 31.3.-31.8.2020, Paris, IEEE, pages 4885-44891, Aug/2020.
Distributed computation and control of robot motion dynamics on FPGAs
Vinzenz Bargsten, José de Gea Fernández
In SN Applied Sciences, Springer Nature, volume 2, number 7, pages 1239-n.n., Jun/2020.
Phobos: A tool for creating complex robot models
Kai von Szadkowski, Simon Reichel
In Journal of Open Source Software, The Open Journal, Journal of Open Source Software, volume 5, number 45, pages 1326, Jan/2020.


Simple and Robust Automatic Detection and Recognition of Human Movement Patterns in Tasks of Different Complexity
Lisa Gutzeit, Marc Otto, Elsa Andrea Kirchner
Editors: Andreas Holzinger, Alan Pope, Hugo Plácido Silva
In Physiological Computing Systems, Springer, pages 39-57, Jul/2019.
Transfer approach for the detection of missed task-relevant events in P300-based brain-computer interfaces
Elsa Andrea Kirchner, Su-Kyoung Kim
In Proceedings in the 9th International IEEE EMBS Conference On Neural Engineering (NER’19), (NER-2019), 20.3.-23.3.2019, San Francisco, CA, IEEE Xplore, pages 134-138, 2019.
Automated Robot Skill Learning from Demonstration for Various Robot Systems
Lisa Gutzeit, Alexander Fabisch, Christoph Petzold, Hendrik Wiese, Frank Kirchner
In KI 2019: Advances in Artificial Intelligence, (KI-2019), 23.9.-26.9.2019, Kassel, Springer, pages 168-181, 2019.


Feel-Good Robotics: Requirements on Touch for Embodiment in Assistive Robotics
Philipp Beckerle, Risto Kõiva, Elsa Andrea Kirchner, Robin Bekrater-Bodmann, Strahinja Dosen, Oliver Christ, David A. Abbink, Claudio Castellini, Bigna Lenggenhager
Editors: Sung-Phil Kim
In Frontiers in Neurorobotics, Frontiers, volume 12, pages o.A., Dec/2018.
Kinematic analysis of a novel parallel 2SPRR+1U ankle mechanism in humanoid robot
Shivesh Kumar, Abhilash Nayak, Heiner Peters, Christopher Schulz, Andreas Mueller, Frank Kirchner
In Advances in Robot Kinematics 2018, (ARK-2018), 01.7.-05.7.2018, Bologna, Springer-Verlag GmbH, series Springer Proceedings in Advanced Robotics, volume 8, pages 431-439, Jul/2018. ISBN: 978-3-319-93188-3.
Automatic Movement Segmentation of Exoskeleton Data
Lisa Gutzeit, Marc Tabie, Elsa Andrea Kirchner
In Conference Proceedings of the 3rd International Mobile Brain/Body Imaging Conference, (MoBI-2018), 11.7.-14.7.2018, Berlin, TU Berlin DepositOnce, pages 62-63, Jul/2018.
The BesMan Learning Platform for Automated Robot Skill Learning
Lisa Gutzeit, Alexander Fabisch, Marc Otto, Jan Hendrik Metzen, Jonas Hansen, Frank Kirchner, Elsa Andrea Kirchner
In Frontiers in Robotics and AI, o.A., volume 5, pages 43, May/2018.
Underactuated gripper design for the assembly of infrastructure in space
Niklas Alexander Mulsow, Peter Kampmann
In Proceedings of the 14th International Symposium on Artificial Intelligence, (iSAIRAS-2018), 04.6.-07.6.2018, Madrid, ESA, 2018.
Conceptual Design of a Variable Stiffness Mechanism in a Humanoid Ankle using Parallel Redundant Actuation
Christoph Stoeffler, Shivesh Kumar, Heiner Peters, Olivier Bruels, Andreas Müller, Frank Kirchner
In IEEE-RAS International Conference on Humanoid Robots, (Humanoids-2018), 06.11.-09.11.2018, IEEE, 2018.


Konstruktion eines zweibeinigen humanoiden Roboters
Heiner Peters, Peter Kampmann, Marc Simnofske
In Proceedings of the 2. VDI Fachkonferenz Humanoide Roboter, 5.12.-6.12.2017, München, VDI Fachkonferenz Humanoide Roboter, Dec/2017.

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