Body-Machine Interfaces (BMI)

We investigate various methods to control the DLR Light-Weight-Robot III with five-finger-hand via brain interfaces.  The LWR's various soft-robotics control schemes are embedded in a human-friendly state-based control architecture which enables the development of complex interaction scenarios. The LWR-III is equipped with the modular DLR five-finger hand for grasping and holding objects. Similar to the robot, this hand is equipped with joint torque sensors for impedance control which makes it robust against uncertainties in the environment such as the position of objects to be grasped.

We use surface EMG for controlling the grasp force of the hand as well as the position of the arm in a user-intuitive manner.  To this end, an adaptive system learns the correspondence between the human hand position and orientation and the muscular activity measured at the skin surface.  Thereby we can control to move the arm and grasp an object in teleoperation / telemanipulation.  Such control schemes are also applicable in rehabilitation and orthoses environments.

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We are furthermore investigating the control of the DLR-LWR-III with five-finger-hand through human cortical implants. In this control scheme, neural signals recorded in the human motor cortex are decoded in continuous motion commands, that are executed by the robot. Additionally a binary state signal is used to trigger grasping actions with the robotic hand. This combination of state-of-the-art robotics and advanced neuro-prosthesis can potentially allow a person with severe physical disabilities to interact with their environment again. Recent results on this research has been published in Nature in 2012. Further information can be found here.


Other interfaces, including invasive communication with the human peripheral nervous system as well as surface EEG control are within the realm of our research spectrum.

A short video showing the German Chancellor Angela Merkel testing the robot that has also been used in our brain-controlled robotics experiments can be found below.

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Picture of  Claudio Castellini

Claudio Castellini

DLR: postdoc
prosthetics and rehabilitation
claudio.castellinidlrde, +49 8153 28-1093
Picture of  Patrick van der Smagt

Patrick van der Smagt

TUM: Director of BRML labs
smagtbrmlorg, +49 89 289-25793
Picture of  Holger Urbanek

Holger Urbanek

DLR: PhD candidate
EMG conditioning
holger.urbanekdlrde, +49 8153 28-2450
Picture of  Jörn Vogel

Jörn Vogel

DLR: PhD candidate
BCI robot control
joern.vogeldlrde, +49 8153 28-2166



2012

    Hochberg LR, Bacher D, Jarosiewicz B, Masse NY, Simeral JD, Vogel J, Haddadin S, Liu J, Cash SS, Smagt P van der, Donoghue JP (2012). Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature. 485 372-377.

2011

    Castellini C, Passig G (2011). Ultrasound image features of the wrist are linearly related to finger positions. Proc. IROS---International Conference on Intelligent Robots and Systems
    Zarka E (2011). Prediction of Finger Movements using Ultrasound Images. Master thesis: University of Applied Sciences Technikum Wien
    Vogel J, Castellini C, Smagt P van der (2011). EMG-Based Teleoperation and Manipulation with the DLR LWR-III. Proc. IROS---International Conference on Intelligent Robots and Systems 672-678.

2010

    Liu J, Simeral JD, Stavisky SD, Bacher D, Vogel J, Haddadin S, Smagt P van der, Hochberg LR, Donoghue JP (2010). Control of a robotic arm using intracortical motor signal by an individual with tetraplegia in the BrainGate2 trial. 40th Annual Meeting in Neuroscience (SFN2010)
    Vogel J, Haddadin S, Simeral J D, Stavisky S D, Bacher D, Hochberg L R, Donoghue J P, Smagt P van der (2010). Continuous Control of the DLR Light-weight Robot III by a human with tetraplegia using the BrainGate2 Neural Interface System. International Symposium on Experimental Robotics (ISER)

2009

    Smagt P van der, Grebenstein M, Urbanek H, Fligge N, Strohmayr M, Stillfried G, Parrish J, Gustus A (2009). Robotics of human movements. Journal of physiology, Paris. 103 (3-5), 119-132.
    Castellini C, Smagt P van der (2009). Surface EMG in Advanced Hand Prosthetics. Biological Cybernetics. 100 (1), 35--47.
    Harms A (2009). Entwicklung einer Elektrode für ein modulares aktives EMG-System. Master thesis: Technische Universität Ilmenau

2008

    Castellini C, Smagt P van der, Sandini G, Hirzinger G (2008). Surface EMG for Force Control of Mechanical Hands. Proceedings - IEEE International Conference on Robotics and Automation 725--730.
    Maier S, Smagt P van der (2008). Surface EMG suffices to classify the motion of each finger independently. Proceedings of MOVIC. 9th International Conference on Motion and Vibration Control

2006

    Bitzer S, Smagt P van der (2006). Learning EMG control of a robotic hand: towards active prostheses. Proceedings 2006 IEEE International Conference on Robotics and Automation 2819-2823.