11 citations · 13 across the 18 of their papers we have counts for
18 papers
Generalizing Manipulation Skills with a Local Coding Agent
Raman Talwar, Elias Nijs, Andreas Verleysen +1
Today, progress in open-weight language models enables systems capable of writing, executing and debugging code while still running on a single workstation. Most language-driven ro…
On the Generalization Capabilities, Design Choices and Limitations of Keypoint Imitation Learning
Thomas Lips, Marco Moletta, Michael C. Welle +2
RGB-based imitation learning requires many demonstrations to generalize to unseen objects or scenes, motivating research into intermediate representations to improve generalization…
Instrumentation for Imitation Learning: Enhancing Training Datasets for Clothes Hanger Insertion
Remko Proesmans, Thomas Lips, Francis wyffels
Large behaviour models have transformed the field of robotic manipulation, but prohibitive data requirements have thus far prevented a revolution similar to vision language models.…
You're Pushing My Buttons: Instrumented Learning of Gentle Button Presses
Raman Talwar, Remko Proesmans, Thomas Lips +2
Learning contact-rich manipulation is difficult from cameras and proprioception alone because contact events are only partially observed. We test whether training-time instrumentat…
Designing Robots with, not for: A Co-Design Framework for Empowering Interactions in Forensic Psychiatry
Qiaoqiao Ren, Remko Proesmans, Arend Pissens +7
Forensic mental health care involves the treatment of individuals with severe mental disorders who have committed violent offences. These settings are often characterized by high l…
A Dataset and Benchmark for Robotic Cloth Unfolding Grasp Selection: The ICRA 2024 Cloth Competition
Victor-Louis De Gusseme, Thomas Lips, Remko Proesmans +59
Robotic cloth manipulation suffers from a lack of standardized benchmarks and shared datasets for evaluating and comparing different approaches. To address this, we created a bench…
Instrumentation for Better Demonstrations: A Case Study
Remko Proesmans, Thomas Lips, Francis wyffels
Learning from demonstrations is a powerful paradigm for robot manipulation, but its effectiveness hinges on both the quantity and quality of the collected data. In this work, we pr…
Self-Mixing Laser Interferometry: In Search of an Ambient Noise-Resilient Alternative to Acoustic Sensing
Remko Proesmans, Thomas Lips, Francis wyffels
Self-mixing interferometry (SMI) has been lauded for its sensitivity in detecting microvibrations, while requiring no physical contact with its target. Microvibrations, i.e., sound…
Self-Mixing Laser Interferometry for Robotic Tactile Sensing
Remko Proesmans, Ward Goossens, Lowiek Van den Stockt +2
Self-mixing interferometry (SMI) has been lauded for its sensitivity in detecting microvibrations, while requiring no physical contact with its target. In robotics, microvibrations…
Touch and Tell: Multimodal Decoding of Human Emotions and Social Gestures for Robots
Qiaoqiao Ren, Remko Proesmans, Yuanbo Hou +2
Human emotions are complex and can be conveyed through nuanced touch gestures. Previous research has primarily focused on how humans recognize emotions through touch or on identify…
Evaluating Text-to-Image Diffusion Models for Texturing Synthetic Data
Thomas Lips, Francis wyffels
Building generic robotic manipulation systems often requires large amounts of real-world data, which can be dificult to collect. Synthetic data generation offers a promising altern…
Automatic Calibration for an Open-source Magnetic Tactile Sensor
Lowiek Van den Stockt, Remko Proesmans, Francis wyffels
Tactile sensing can enable robots to perform complex, contact-rich tasks. Magnetic sensors offer accurate three-axis force measurements while using affordable materials. Calibratin…
Learning Keypoints for Robotic Cloth Manipulation using Synthetic Data
Thomas Lips, Victor-Louis De Gusseme, Francis wyffels
Assistive robots should be able to wash, fold or iron clothes. However, due to the variety, deformability and self-occlusions of clothes, creating robot systems for cloth manipulat…
Seamless Integration of Tactile Sensors for Cobots
Remko Proesmans, Francis wyffels
The development of tactile sensing is expected to enhance robotic systems in handling complex objects like deformables or reflective materials. However, readily available industria…
Augmenting Off-the-Shelf Grippers with Tactile Sensing
Remko Proesmans, Francis wyffels
The development of tactile sensing and its fusion with computer vision is expected to enhance robotic systems in handling complex tasks like deformable object manipulation. However…
Revisiting Proprioceptive Sensing for Articulated Object Manipulation
Thomas Lips, Francis wyffels
Robots that assist humans will need to interact with articulated objects such as cabinets or microwaves. Early work on creating systems for doing so used proprioceptive sensing to…
CenDerNet: Center and Curvature Representations for Render-and-Compare 6D Pose Estimation
Peter De Roovere, Rembert Daems, Jonathan Croenen +3
We introduce CenDerNet, a framework for 6D pose estimation from multi-view images based on center and curvature representations. Finding precise poses for reflective, textureless o…
Dataset of Industrial Metal Objects
Peter De Roovere, Steven Moonen, Nick Michiels +1
We present a diverse dataset of industrial metal objects. These objects are symmetric, textureless and highly reflective, leading to challenging conditions not captured in existing…