Master Thesis/Internship: “Quaternion EKF for State Estimation of the RH5 Humanoid Robot Performing Dynamic Walking”

In order to strengthen our dedicated team in the Robotics Innovation Center (RIC) research department in Bremen we are looking for a  

Master Thesis/Internship 

(full-time/part-time, 3 – 9 months) 

“Quaternion EKF for State Estimation of the RH5 Humanoid Robot Performing Dynamic Walking”

The Robotics Innovation Center research department, headed by Prof. Dr. Dr. h.c. Kirchner, develop robot systems that are used for complex tasks on land, under water, in the air, and in space. The recently established underactuated lab at DFKI-RIC is looking for outstanding students to join us in pushing the boundaries of highly dynamic and agile robots.


Mobile legged robots rely on state estimation algorithms to determine the robot position and orientation in the world reference frame. For this purpose, multiple sensors such as inertial measurement unit, joint encoders and contact sensors to detect foot contact with the ground are commonly employed. The accuracy of the state estimation algorithm plays a crucial role in the control and locomotion robustness of the robotic system. Sensor fusion techniques relying on Kalman filter approaches have been widely employed in literature to estimate the robot state. The goal of this thesis is to implement a sensor fusion technique such as the Quaternion EKF [1] for the humanoid robot RH5 and conduct an experimental evaluation in comparison with the InEKF [2] state of the art framework. Ground truth from a motion capture system will be used to evaluate the two approaches and investigate the limitations of state estimation algorithms on bipedal robots while performing various legged motions such as dynamic walking.

Prior Knowledge:

lMathematical: linear algebra, basic control theory.

lProgramming: C/C++, Python, Git, ROS / RoCK, ideally experience with robotic simulation software (e.g. Raisim, Pybullet etc).

Related Work:

1)J. L. Marins, Xiaoping Yun, E. R. Bachmann, R. B. McGhee and M. J. Zyda, "An extended Kalman filter for quaternion-based orientation estimation using MARG sensors," Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180), Maui, HI, USA, 2001, pp. 2003-2011 vol.4, doi: 10.1109/IROS.2001.976367.

2)Hartley R, Ghaffari M, Eustice RM, Grizzle JW. Contact-aided invariant extended Kalman filtering for robot state estimation. The International Journal of Robotics Research. 2020;39(4):402-430. doi:10.1177/0278364919894385 


Please contact Mihaela Popescu (Phone: +49 421 17845 4141) for further information and send your application via E-Mail to

last updated 31.03.2023
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