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cs.RO2024

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…

cs.RO2024

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…

cs.RO2024

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…

cs.RO2024

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…

cs.RO2024

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…