9 citations · 16 across the 10 of their papers we have counts for
7 papers · 1 filter
Autonomous Iterative Motion Learning (AI-MOLE) of a SCARA Robot for Automated Myocardial Injection
Michael Meindl, Raphael Mönkemöller, Thomas Seel
Stem cell therapy is a promising approach to treat heart insufficiency and benefits from automated myocardial injection which requires highly precise motion of a robotic manipulato…
Dispelling Four Challenges in Inertial Motion Tracking with One Recurrent Inertial Graph-based Estimator (RING)
Simon Bachhuber, Ive Weygers, Thomas Seel
In this paper, we extend the Recurrent Inertial Graph-based Estimator (RING), a novel neural-network-based solution for Inertial Motion Tracking (IMT), to generalize across a large…
A Soft Robotic System Automatically Learns Precise Agile Motions Without Model Information
Simon Bachhuber, Alexander Pawluchin, Arka Pal +2
Many application domains, e.g., in medicine and manufacturing, can greatly benefit from pneumatic Soft Robots (SRs). However, the accurate control of SRs has remained a significant…
Towards Optimized Parallel Robots for Human-Robot Collaboration by Combined Structural and Dimensional Synthesis
Aran Mohammad, Thomas Seel, Moritz Schappler
Parallel robots (PR) offer potential for human-robot collaboration (HRC) due to their lower moving masses and higher speeds. However, the parallel leg chains increase the risks of…
SPONGE: Open-Source Designs of Modular Articulated Soft Robots
Tim-Lukas Habich, Jonas Haack, Mehdi Belhadj +3
Soft-robot designs are manifold, but only a few are publicly available. Often, these are only briefly described in their publications. This complicates reproduction, and hinders th…
AI-MOLE: Autonomous Iterative Motion Learning for Unknown Nonlinear Dynamics with Extensive Experimental Validation
Michael Meindl, Simon Bachhuber, Thomas Seel
This work proposes Autonomous Iterative Motion Learning (AI-MOLE), a method that enables systems with unknown, nonlinear dynamics to autonomously learn to solve reference tracking…