38 citations · 62 across the 7 of their papers we have counts for
7 papers
Learning Controlled Separation of Small Objects Between Two Fingers with a Tactile Skin
Ulf Kasolowsky, Berthold Bäuml
We introduce and solve the novel task of controlled separation of small objects with two fingers of a multi-purpose robotic hand: after grasping into a box of small objects, the ta…
Denoising Particle Filters: Learning State Estimation with Single-Step Objectives
Lennart Röstel, Berthold Bäuml
Learning-based methods commonly treat state estimation in robotics as a sequence modeling problem. While this paradigm can be effective at maximizing end-to-end performance, models…
Self-Contained Calibration of an Elastic Humanoid Upper Body Using Only a Head-Mounted RGB Camera
Johannes Tenhumberg, Dominik Winkelbauer, Darius Burschka +1
When a humanoid robot performs a manipulation task, it first makes a model of the world using its visual sensors and then plans the motion of its body in this model. For this, prec…
Calibration of an Elastic Humanoid Upper Body and Efficient Compensation for Motion Planning
Johannes Tenhumberg, Berthold Bäuml
High absolute accuracy is an essential prerequisite for a humanoid robot to autonomously and robustly perform manipulation tasks while avoiding obstacles. We present for the first…
Efficient Learning of Fast Inverse Kinematics with Collision Avoidance
Johannes Tenhumberg, Arman Mielke, Berthold Bäuml
Fast inverse kinematics (IK) is a central component in robotic motion planning. For complex robots, IK methods are often based on root search and non-linear optimization algorithms…
Combining Shape Completion and Grasp Prediction for Fast and Versatile Grasping with a Multi-Fingered Hand
Matthias Humt, Dominik Winkelbauer, Ulrich Hillenbrand +1
Grasping objects with limited or no prior knowledge about them is a highly relevant skill in assistive robotics. Still, in this general setting, it has remained an open problem, es…
Learning Purely Tactile In-Hand Manipulation with a Torque-Controlled Hand
Leon Sievers, Johannes Pitz, Berthold Bäuml
We show that a purely tactile dextrous in-hand manipulation task with continuous regrasping, requiring permanent force closure, can be learned from scratch and executed robustly on…