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Hubert Zangl

12 accepted papers

2026

CapTac: Robust Capacitive Sensing for Distributed Force Mapping in Parallel Robotic Grasping

Serkan Ergun, Rishabh B. Mishra, Narendiran Anandan, Tobias Mitterer, Virgilio Mattoli, Hubert Zangl
RA-L 2026

For reliably grasping sensitive and delicate objects, measuring the distribution of normal and shear forces across contact areas is crucial-particularly for slip detection and preventing damage of delicate objects. This necessitates sensors that are easily integrated into robotic fingers (small form

Cited by 1Source ↗code ↗Scholar ↗
2023

Wireless Capacitive Tactile Sensor Arrays for Sensitive/Delicate Robot Grasping

Serkan Ergun, Tobias Mitterer, Sherjeel Khan, Narendiran Anandan, Rishabh B. Mishra, Jürgen Kosel +1
IROS 2023poster

Uncertainties in grasp prediction for unknown, arbitrarily shaped objects in cluttered environments and un- certainty of the kinematics (e.g., series elastic robots or soft robots) can lead to poor grasps. For delicate objects, such poor grasps may damage the objects when they are dropped or when hi…

Cited by 3Source ↗Scholar ↗
2022

CapSense: A Real-Time Capacitive Sensor Simulation Framework for Physical Human-Robot Interaction

Christian Schöffmann, Zackory Erickson, Hubert Zangl
RA-L 2022

This letter presents CapSense, a real-time open-source capacitive sensor simulation framework for robotic applications. CapSense provides raw data of capacitive proximity sensors based on a fast and efficient 3D finite-element method (FEM) implementation. The proposed framework is interfaced to off-

Cited by 2Source ↗Scholar ↗
2022

Evaluation of On-Robot Capacitive Proximity Sensors with Collision Experiments for Human-Robot Collaboration

Hosam Alagi, Serkan Ergun, Yitao Ding, Tom P. Huck, Ulrike Thomas, Hubert Zangl +1
IROS 2022poster

A robot must comply with very restrictive safety standards in close human-robot collaboration applications. These standards limit the robot's performance because of speed reductions to avoid potentially large forces exerted on humans during collisions. On-robot capacitive proximity sensors (CPS) can…

Cited by 5Source ↗Scholar ↗
2021

A Unified Perception Benchmark for Capacitive Proximity Sensing Towards Safe Human-Robot Collaboration (HRC)

Serkan Ergun, Yitao Ding, Hosam Alagi, Christian Schöffmann, Barnaba Ubezio, Gergely Soti +6
ICRA 2021poster

During the co-presence of human workers and robots, measures are required to avoid injuries from undesired contacts. Capacitive Proximity Sensors (CPSs) offer a cost-effective solution to cover the entire robot manipulator with fast close-range perception for HRC tasks, closing the perception gap be…

Cited by 13Source ↗Scholar ↗
2021

Radar Based Target Tracking and Classification for Efficient Robot Speed Control in Fenceless Environments

Barnaba Ubezio, Christian Schöffmann, Lucas Wohlhart, Stephan Mülbacher-Karrer, Hubert Zangl, Michael Hofbaur
IROS 2021poster

Awareness of its surroundings is a crucial capability for a robot meant to be working alongside other robots or human operators. When considering safety norms and modalities, in particular the Speed and Separation Monitoring (SSM), proper proximity information can make the difference in the overall…

Cited by 12Source ↗Scholar ↗
2021

Virtual Radar: Real-Time Millimeter-Wave Radar Sensor Simulation for Perception-Driven Robotics

Christian Schöffmann, Barnaba Ubezio, Christoph Böhm, Stephan Mühlbacher-Karrer, Hubert Zangl
RA-L 2021

This article presents ViRa <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> Available online: https://vira.aau.at/., a real-time open-source mi

Cited by 29Source ↗Scholar ↗
2020

A Model-Based Sensor Fusion Approach for Force and Shape Estimation in Soft Robotics

Stefan Escaida Navarro, Steven Nagels, Hosam Alagi, Lisa-Marie Faller, Olivier Goury, Thor Morales Bieze +6
RA-L 2020

In this letter, we address the challenge of sensor fusion in Soft Robotics for estimating forces and deformations. In the context of intrinsic sensing, we propose the use of soft capacitive sensing to find a contact's location, and the use of pneumatic sensing to estimate the force intensity and the

Cited by 63Source ↗Scholar ↗
2020

Radar Sensors in Collaborative Robotics: Fast Simulation and Experimental Validation

Christian Stetco, Barnaba Ubezio, Stephan Mühlbacher-Karrer, Hubert Zangl
ICRA 2020poster

With the availability of small system in package realizations, radar systems become more and more attractive for a variety of applications in robotics, in particular also for collaborative robotics. As the simulation of robot systems in realistic scenarios has become an important tool, not only for…

Cited by 34Source ↗Scholar ↗
2019

Design of a Novel Gripper System with 3D- and Inkjet-printed Multimodal Sensors for Automated Grasping of a Forestry Robot

Lisa-Marie Faller, Christian Stetco, Hubert Zangl
IROS 2019poster

Future industrial robotic systems increasingly rely on automation of dangerous and tedious tasks. The acquisition of diverse and partially redundant information using reliable and rugged multimodal sensors helps to improve the safety an dependability of such systems. In this paper we propose proximi…

Cited by 25Source ↗Scholar ↗
2017

Contactless Control of a Kinematically Redundant Serial Manipulator Using Tomographic Sensors

Stephan Mühlbacher-Karrer, Mathias Brandstötter, Dominik Schett, Hubert Zangl
RA-L 2017

For intelligent robots sharing their workspace with humans, a reliable robot perception is mandatory. Moreover, the ease of interaction between a human and a robot in a shared workspace is indispensable. We propose a touchless motion guidance based on 2-D spatial information from a capacitive tomogr

Cited by 13Source ↗Scholar ↗
2015

Responsive fingers — capacitive sensing during object manipulation

Stephan Mühlbacher-Karrer, Andre Gaschler, Hubert Zangl
IROS 2015poster

We present a novel approach of active object categorization based on an iterative Bayesian method using capacitive sensing during object manipulation. The approach uses a novel type of capacitive sensor, which can measure internal properties of materials that are inaccessible to vision or tactile se…

Cited by 21Source ↗Scholar ↗