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Karel Kellens

Prof. dr. ing. at KU Leuven

KU Leuven
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Belgium

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About

Prof. dr. ing. Karel Kellens is a faculty member at KU Leuven in Belgium. His research primarily focuses on the design and evaluation of innovative robotic systems, including haptic teleoperation and deep learning techniques for robotic grasping. He is also engaged in the automated assembly of non-rigid objects, contributing to advancements in industrial automation and robotics.

Positions (2)

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Karel Kellens

University Name
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KU Leuven

Mechatronic Design of Smart Robotic Tooling and Systems

The ACRO research group at KU Leuven, located at the Diepenbeek campus, is offering a PhD position focused on the mechatronic design of smart robotic tooling and systems. ACRO, part of the Faculty of Engineering Technology and the M&A core lab of FlandersMake@KULeuven, brings together expertise from Mechanical Engineering and Computer Science to advance automation, computer vision, and robotics. The group collaborates closely with Flemish companies and stakeholders, conducting applied research that translates academic innovation into industrial and societal impact across manufacturing, agriculture, logistics, healthcare, construction, and waste recycling. As a PhD candidate, you will contribute to the development of smart, adaptive end-effectors (robot grippers) and robotic systems that integrate advanced sensors, precision mechanics, and intelligent control. The goal is to create robotic technologies that not only move but also 'think' and feel, opening new possibilities for automation in diverse sectors such as manufacturing, agriculture, and construction. The project emphasizes the design and implementation of mechatronic solutions that address real-world challenges and enable next-generation mobile robots. Applicants should have a Master's degree in Electromechanics, Mechatronics, Robotics, Mechanical Engineering, or a related discipline, with experience in mechanical and mechatronic design. Strong analytical skills and a passion for applied research are essential. The position offers a stimulating, international research environment, opportunities for collaboration with leading companies and research institutes, and supervision by experienced professors. KU Leuven provides a competitive salary and a flexible working environment, supporting diversity and inclusion in all aspects of academic life. The application deadline is January 16, 2026. Interested candidates should apply online via the KU Leuven jobsite. For further information, you may contact Prof. dr. ing. Karel Kellens or Prof. dr. ir. Eric Demeester. KU Leuven is committed to equal opportunity and encourages applicants from all backgrounds.

7 months ago

Articles (3)

Design and Evaluation of an Intuitive Haptic Teleoperation Control System for 6-DoF Industrial Manipulators

Industrial robots are capable of performing automated tasks repeatedly, reliably and accurately. However, in some scenarios, human-in-the-loop control is required. In this case, having an intuitive system for moving the robot within the working environment is crucial. Additionally, the operator should be aided by sensory feedback to obtain a user-friendly robot control system. Haptic feedback is one way of achieving such a system. This paper designs and assesses an intuitive teleoperation system for controlling an industrial 6-DoF robotic manipulator using a Geomagic Touch haptic interface. The system utilises both virtual environment-induced and physical sensor-induced haptic feedback to provide the user with both a higher amount of environmental awareness and additional safety while manoeuvering the robot within its working area. Different tests show that the system is capable of fully stopping the manipulator without colliding with the environment, and preventing it from entering singularity states with Cartesian end effector velocities of up to 0.25 m/s. Additionally, an operator is capable of executing low-tolerance end effector positioning tasks (∼0.5 mm) with high-frequency control of the robot (∼100 Hz). Fourteen inexperienced volunteers were asked to perform a typical object removal and writing task to gauge the intuitiveness of the system. It was found that when repeating the same test for a second time, the participants performed 22.2% faster on average. The results for the second attempt also became significantly more consistent between participants, as the inter quartile range dropped by 82.7% (from 52 s on the first attempt to 9 s on the second).

Year:

2023

Collaborators (2)

Franz Dietrich

Technische Universität Berlin

GERMANY

Eric Demeester

Katholieke Universiteit Leuven

BELGIUM
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