11 citations · 20 across the 6 of their papers we have counts for
9 papers · 1 filter
Heterogeneous Full-body Control of a Mobile Manipulator with Behavior Trees
Marco Iannotta, David Cáceres Domínguez, Johannes A. Stork +2
Integrating the heterogeneous controllers of a complex mechanical system, such as a mobile manipulator, within the same structure and in a modular way is still challenging. In this…
Transferring Knowledge for Reinforcement Learning in Contact-Rich Manipulation
Quantao Yang, Johannes A. Stork, Todor Stoyanov
In manufacturing, assembly tasks have been a challenge for learning algorithms due to variant dynamics of different environments. Reinforcement learning (RL) is a promising framewo…
Multi-Object Rearrangement with Monte Carlo Tree Search:A Case Study on Planar Nonprehensile Sorting
Haoran Song, Joshua A. Haustein, Weihao Yuan +4
In this work, we address a planar non-prehensile sorting task. Here, a robot needs to push many densely packed objects belonging to different classes into a configuration where the…
Object Placement Planning and Optimization for Robot Manipulators
Joshua A. Haustein, Kaiyu Hang, Johannes Stork +1
We address the problem of motion planning for a robotic manipulator with the task to place a grasped object in a cluttered environment. In this task, we need to locate a collision-…
Data-Driven Model Predictive Control for Food-Cutting
Ioanna Mitsioni, Yiannis Karayiannidis, Johannes A. Stork +1
Modelling of contact-rich tasks is challenging and cannot be entirely solved using classical control approaches due to the difficulty of constructing an analytic description of the…
Learning Manipulation States and Actions for Efficient Non-prehensile Rearrangement Planning
Joshua A. Haustein, Isac Arnekvist, Johannes Stork +2
This paper addresses non-prehensile rearrangement planning problems where a robot is tasked to rearrange objects among obstacles on a planar surface. We present an efficient planni…