Inhalt des Dokuments
Identification of Beneficial Morphological Computation on Soft Hands
[1]- © Robotics
Motivation
Compliance in soft hands can be both beneficial and detrimental to functionality. Although recent work has shown the benefits of compliance to object and environment geometry, there is little work in identifying and avoiding the negative aspects of compliance while controlling soft hands. However, a planner or a feedback-controller that exploits compliance should avoid the regions of detrimental morphological computation and guide the interactions to the favorable ones.
Luckily recent work in simulation has shown promising results in differentiating between beneficial/detrimental morphological computations. The challenge ahead is to whether these results can be transferred to real systems. Our lab's work in hand sensorization is a possible tool in this path.
Description of Work
In this thesis, the student will extend the analysis tools that were
used for the grasping simulation data to real life scenarios. He/she
will first test the analysis in simulation with different input
modalities that can be generated in real life. If successful, direct
application to the robot will be the next step. If not successful, the
analysis will be altered to exploit the sensorization of the real
hand.
Requirements
Strong C++ programming background
Robotics (ROS)
Further reading
[1]
Vincent Wall, Gabriel Zoeller, Oliver Brock. A Method for Sensorizing
Soft Actuators and Its Application to the RBO Hand 2. IEEE/RSJ
International Conference on Robotics and Automation, 2017
Full Thesis (PDF) [2]
People
Marlon Kupfer
Vincent Wall [3]
Oliver Brock [4]
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