TU Berlin

Robotics and Biology LaboratoryResearch

Fachgebietslogo RBO

Page Content

to Navigation

Interactive Perception

Action is a crucial part of the perceptual process. Humans interact with their environment constantly to reveal information and use the interaction to understand the consequences of their actions in the world. Interactive Perception exploits these ideas to build autonomous mobile manipulators that use interactions to perceive, understand and manipulate their environment. more to: Interactive Perception

Manipulation Planning

Brushing teeth, eating, opening a door: humans interact with the environment countless times each day without thinking of it. Manipulation planning requires the understanding of Object, Robot, and Environment (ORE) interactions. We research the "ORE triangle" to advance the field and shift the manipulation planning paradigm toward new and exciting realms. more to: Manipulation Planning

Soft Hands

We design, build, and use soft robotic hands, like the RBO Hand 2. Made from rubber and actuated pneumatically, they are highly compliant and extremely robust. With them we can reliably grasp objects with uncertain geometries and positions, by offloading some perceptual difficulties to the morphological computation of the hand itself. more to: Soft Hands

Sensorization of Soft Hands and Actuators

Soft robotic actuators introduce novel challenges for their sensorization. Due to the high flexibility and compliance of soft material robots, traditional approaches that rely on joint encoders and torque measurements are no longer applicable. Instead, we develop novel sensor technologies and research clever ways of combining sensor measurements with computation to extract relevant feedback. more to: Sensorization of Soft Hands and Actuators

In-Hand Manipulation

Unlike most robot grippers, human hands are versatile manipulators: they are soft, compliant, dexterous, and can be used for multiple tasks at once. We want robotic hands to be similarly versatile. Therefore, investigations of different feature encodings, sample-efficient learning algorithms, appropriate simulation environments and various kinds of hand sensorization are employed to tackle the problem of In-Hand-Manipulation. more to: In-Hand Manipulation

Protein Structure Prediction

What shape does a protein take when it folds? This questions have preoccupied researchers for decades. We are building algorithms that leverage experimental and evolutionary data to answer this question, and predict the structures of proteins from their sequences. more to: Protein Structure Prediction


Quick Access

Schnellnavigation zur Seite über Nummerneingabe