3 citations · 4 across the 3 of their papers we have counts for
8 papers · 1 filter
Learning a Generative Transition Model for Uncertainty-Aware Robotic Manipulation
Lars Berscheid, Pascal Meißner, Torsten Kröger
Robot learning of real-world manipulation tasks remains challenging and time consuming, even though actions are often simplified by single-step manipulation primitives. In order to…
Jerk-limited Real-time Trajectory Generation with Arbitrary Target States
Lars Berscheid, Torsten Kröger
We present Ruckig, an algorithm for Online Trajectory Generation (OTG) respecting third-order constraints and complete kinematic target states. Given any initial state of a system…
Learning Robot Trajectories subject to Kinematic Joint Constraints
Jonas C. Kiemel, Torsten Kröger
We present an approach to learn fast and dynamic robot motions without exceeding limits on the position , velocity , acceleration and jerk of each robo…
Self-supervised Learning for Precise Pick-and-place without Object Model
Lars Berscheid, Pascal Meißner, Torsten Kröger
Flexible pick-and-place is a fundamental yet challenging task within robotics, in particular due to the need of an object model for a simple target pose definition. In this work, t…
TrueÆdapt: Learning Smooth Online Trajectory Adaptation with Bounded Jerk, Acceleration and Velocity in Joint Space
Jonas C. Kiemel, Robin Weitemeyer, Pascal Meißner +1
We present TrueÆdapt, a model-free method to learn online adaptations of robot trajectories based on their effects on the environment. Given sensory feedback and future waypoints o…
General Hand Guidance Framework using Microsoft HoloLens
David Puljiz, Erik Stöhr, Katharina S. Riesterer +2
Hand guidance emerged from the safety requirements for collaborative robots, namely possessing joint-torque sensors. Since then it has proven to be a powerful tool for easy traject…