Marcin Odelga

Address: Spemannstr. 44
72076 Tübingen
Room number: 2.VR.01
Phone: +49 7071 601 227
Fax: +49 7071 601 616
E-Mail: marcin.odelga


Picture of Odelga, Marcin

Marcin Odelga

Position: PhD Student  Unit: Bülthoff

I am a Ph.D. student in the Autonomous Robotics and Human-Machine Systems at Max Planck Institute for Biological Cybernetics.


My reserch focuses mainly on development of an UAV platform for haptic teleoperation with on-board computation and sensing using an RGB-D sensor.

Development of an UAV platform for haptic teleoperation with on-board computation and sensing using an RGB-D camera.



An Unmanned Aerial Vehicle (UAV) haptic teleoperation platform is an aerial robot that provides haptic and visual feedbacks to the human operator. Provided feedbacks decrease the operator effort to perform desired tasks. Most of existing platforms rely on external tracking systems and computational power which currently limit their possible application to laboratory/structured environment.



To increase the range of possible applications we aim to develop an UAV platform that could be teleoperated with a haptic device independently of external sensors and computational units. This will allow to perform tasks in most of indoor and subsequently outdoor spaces. With semi autonomous behaviors such as obstacle avoidance, the robot will aid - but not limit - the role of the human operator.



Integration of an on-board computational unit with the RGB-D sensor and inertia measurement unit (IMU) on-board an UAV will provide the testbed platform to develop control and estimation algorithms. Fusion of visual and inertia data through Kalman filtering will be enacted to estimate sensible quantities independently of external equipment. Advanced filtering methods, such as the Bin-Occupancy filter, can be used to build a local obstacle map and implement obstacle avoidance. All the estimated information will be used in a robust control scheme to achieve stable flight of the platform.


Current progress

We have designed and implemented the mechanical platform that integrates all the required equipment (e.g.: CPU and sensors). The robot is ready to perform the estimation and control tasks using the on-board computational unit only. We have run the software for localization using the RGB-D sensor, integration with the low-level flight controller and with the haptic teleoperation interface. We have performed first successful flights and collect initial data.

Currently the obstacle detection and avoidance algorithm is under development.

References per page: Year: Medium:

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Articles (1):

Chriette A, Plestan F, Castañeda H, Pal M, Guillo M, Odelga M, Rajappa S and Chandra R (September-2016) Adaptive robust attitude control for UAVs: Design and experimental validation International Journal of Adaptive Control and Signal Processing 30(8-10) 1478–1493.

Conference papers (3):

Odelga M, Stegagno P and Bülthoff HH (July-13-2016) A fully actuated quadrotor UAV with a propeller tilting mechanism: Modeling and control, IEEE International Conference on Advanced Intelligent Mechatronics (AIM 2016), IEEE, Piscataway, NJ, USA, 306-311.
Odelga M, Bülthoff HH and Stegagno P (May-2016) Obstacle Detection, Tracking and Avoidance for a Teleoperated UAV, IEEE International Conference on Robotics and Automation (ICRA 2016), IEEE, Piscataway, NJ, USA, 2984-2990.
Odelga M, Stegagno P, Bülthoff HH and Ahmad A (November-2015) A Setup for multi-UAV hardware-in-the-loop simulations, 3rd Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS 2015), IEEE, Piscataway, NJ, USA, 204-210.

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Last updated: Tuesday, 18.11.2014