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TU Berlin

Inhalt des Dokuments

Sensorized In-Hand Manipulation

Lupe

Master Thesis


Motivation

The RBO Hand 2 is a highly compliant soft robotic hand. Its actuators passively adapt their shape to different objects and the environment. Even though the control of the pneumatic hand is relatively simple, it is capable of complex in-hand manipulation: Ball Rotation (Video)Pen Flip (Video).

 

The recent addition of liquid metal strain sensors has created the opportunity to obtain better feedback about the current state of the hand.

The goal of this thesis is to utilize this new sensor information to make the execution of different in-hand manipulation tasks more robust.

 


Description of Work

For the thesis you will implement a controller for the RBO Hand, that is capable of performing different in-hand manipulation tasks (like twisting a ball or flipping a pen), while taking into account the data from the strain sensors.

By distinguishing successful from unsuccessful attempts in the sensor data, and identifying appropriate reaction to common error cases, the overall robustness of the manipulation will be improved.

Finally, the controller should be able to perform these tasks reliably, even external disturbances occur.


 

Requirements

Solid object oriented programming skills (C++ or Python)

Robotics (ROS) and control

 

People

Vincent Wall

Oliver Brock

 

 

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