8 citations · 9 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
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…
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…
Learning Keypoints from Synthetic Data for Robotic Cloth Folding
Thomas Lips, Victor-Louis De Gusseme, Francis wyffels
Robotic cloth manipulation is challenging due to its deformability, which makes determining its full state infeasible. However, for cloth folding, it suffices to know the position…