Robotics and Biology Laboratory

Adrian Sieler

Short CV

  • 06.2019 - present
  • 04.2016 - 03.2019
    • MSc Mathematics in Data Science - TU Munich
      • 04.2018 - 12.2018
        Master Thesis, Siemens AG - Corporate Technology: Mechatronic Systems
        Topic: Simulation-Based Reinforcement Learning of Complex Reflexes for Low-Level Robotic Systems
  • 08.2018 - 05.2019
  • 10.2012-04.2016
    • BSc Mathematics - TU Munich
      • 12.2015 - 03.2016  
        Bachelor Thesis
        Topic: Refinement and Coarsening of Online-Offline Data Mining Methods with Sparse Grids
Gebäude MAR
Raum MAR 5.065


© Felix Noak

Dexterous and Sensorized Soft Robotic Hands

Inspired by human grasping and manipulation capabilities, we build anthropomorphic soft robotic hands with a high degree of dexterity to enable robust interactions with the environment. We develop new sensor technologies that work with the highly compliant hands, while still providing useful sensor feedback. At the same time, we further increase the robustness of soft hands by devising control methods that reduce perceptual, model, and motion uncertainty through haptic feedback.