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)
“Probabilistic Foot Contact Detection of a Quadruped Robot using Proprioceptive Sensors”
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.
Topic:
Mobile legged robots rely on state estimation algorithms to determine the robot position and orientation in the world reference frame. The robot state can be estimated using proprioceptive sensors such as inertial measurement unit (IMU) and leg odometry when the foot is in contact with the ground. The contact information can be obtained through contact sensors mounted under the feet or torque sensors mounted in the robot leg joints. Accurate contact detection plays a crucial role in proprioceptive state estimation, therefore a proper contact detection strategy for legged robots is required. The goal of this thesis is to develop a probabilistic contact estimation technique for a quadruped robot using leg kinematics and joint torque sensors. The framework will be validated on a quadruped performing various gaits at different speeds.
Prior Knowledge:
Mathematical: linear algebra, basic control theory.
Programming: C/C++, Python, Git, ROS / RoCK, ideally experience with robotic simulation software (e.g. Raisim, Pybullet etc).
Related Work:
M. Camurri et al., "Probabilistic Contact Estimation and Impact Detection for State Estimation of Quadruped Robots," in IEEE Robotics and Automation Letters, vol. 2, no. 2, pp. 1023-1030, April 2017, doi: 10.1109/LRA.2017.2652491.
Hwangbo, Jemin & Bellicoso, Dario & Fankhauser, Péter & Hutter, Marco. (2016). Probabilistic foot contact estimation by fusing information from dynamics and differential/forward kinematics. 3872-3878. 10.1109/IROS.2016.7759570.
Please contact Mihaela Popescu for further information and send your application via E-Mail to Mihaela.Popescu@dfki.de.
Deutsches Forschungszentrum für Künstliche Intelligenz GmbH
Research Department
Robotics Innovation Center
Robert-Hooke-Str. 1
28359 Bremen, Germany
www.dfki.de/ric
Phone: +49 421 17845 4141
Mihaela.Popescu@dfki.de
