Michel R. Vogt — accepted AI-conference papers

2025

ORCA: An Open-Source, Reliable, Cost-Effective, Anthropomorphic Robotic Hand for Uninterrupted Dexterous Task Learning

Clemens C. Christoph, Maximilian Eberlein, Filippos Katsimalis, Arturo Roberti, Aristotelis Sympetheros, Michel R. Vogt +5

IROS 2025

General-purpose robots should possess humanlike dexterity and agility to perform tasks with the same versatility as us. A human-like form factor further enables the use of vast datasets of human-hand interactions. However, the primary bottleneck in dexterous manipulation lies not only in software bu

Cited by 23 Source ↗Scholar ↗

2024

High-Frequency Capacitive Sensing for Electrohydraulic Soft Actuators

Michel R. Vogt, Maximilian Eberlein, Clemens C. Christoph, Felix Baumann, Fabrice Bourquin, Wim Wende +3

IROS 2024poster

The need for compliant and proprioceptive actuators has grown more evident in pursuing more adaptable and versatile robotic systems. Hydraulically Amplified Self-Healing Electrostatic (HASEL) actuators offer distinctive advantages with their inherent softness and flexibility, making them promising c…

Cited by 2 Source ↗Scholar ↗

2024

Self-Sensing Feedback Control of an Electrohydraulic Robotic Shoulder

Clemens C. Christoph, Amirhossein Kazemipour, Michel R. Vogt, Yu Zhang, Robert K. Katzschmann

ICRA 2024poster

The human shoulder, with its glenohumeral joint, tendons, ligaments, and muscles, allows for the execution of complex tasks with precision and efficiency. However, current robotic shoulder designs lack the compliance and compactness inherent in their biological counterparts. A major limitation of th…

Cited by 1 Source ↗Scholar ↗