For the fifth time, the MLSS takes place in Tübingen
Swallowable biopsy robot of doom
Scientists under the lead of Metin Sitti at the Max Planck Institute for Intelligent Systems in Stuttgart have recently constructed a material system that provides dynamic self-assembly.
To be alive, biologically speaking, means to be able to breath, to eat, to drink, to grow, to age, and, perhaps, to move. Food is the energy source, and metabolism translates the stored chemical energy into biochemical energy to sustain live functions. The physical abstraction of this energy transduction by living organisms is extremely simple: it involves energy input and energy dissipation. This mechanistic view of life looks almost trivial, but to apply this type of thinking in the design of materials and material systems is non-trivial. Scientists under the lead of Metin Sitti at the Max Planck Institute for Intelligent Systems in Stuttgart have recently constructed a material system that requires continuous magnetic energy input and viscous dissipation to maintain its spatiotemporal patterns, and the term usually used to describe this type of material system in the research community is dynamic self-assembly.
at the 2017 IEEE/RAS International Conference on Robotics and Automation
The paper "Probabilistic Articulated Real-Time Tracking for Robot Manipulation" by Cristina Garcia Cifuentes, Jan Issac, Manuel Wüthrich, Stefan Schaal and Jeannette Bohg was finalist for the Best Robotic Vision paper at the 2017 IEEE/RAS International Conference on Robotics and Automation.
Penn alumnus Zoey Davidson, now a postdoc at the Max Planck Institute for Intelligent Systems in Germany, had been experimenting with Sunset Yellow, a dye that gives Doritos and orange soft drinks their bright colors, when he accidentally spilled some of the material.
Robust and real-time Bayesian articulated object tracking methods, implemented in C++ and CUDA.
We release open-source code and data sets on Bayesian articulated object tracking. The library contains approaches towards problems ranging from single object tracking to full robot arm pose estimation. The data sets allow the quantitative evaluation of alternative approaches thanks to accurate ground-truth annotations.
An elastic membrane covered with tiny fibres paired with a pressure differential enables a new soft gripper system with a high adhesion performance even on curved surfaces
Robots generally need a gripper that adapts to three-dimensional surfaces. Such a gripper needs to be soft to adapt to a great variety of geometries, but not too soft, as it will detach easily and not be able to bear weight for very long. Researchers working with Metin Sitti at the Max Planck Institute for Intelligent Systems in Stuttgart developed a membrane equipped with microscopic fibres inspired by the fine hairs on a gecko's foot and attached it to a suction cup-like flexible body. An internal pressure differential ensures perfect conformation of the flexible gripper to a wide variety of surfaces and equally distributes the load over the entire contact interface. As a result, the researchers suppressed load induced stress concentrations at the edges, which strongly reduced the adhesion. The gripper demonstrates a 14-times higher adhesion than grippers without this load sharing mechanism.