Victor-Louis De Gusseme
Papers
6
Total Citations
34
H-Index
4
About
Victor-Louis De Gusseme is a leading researcher in robotic cloth manipulation, a field critical for developing assistive robots capable of washing, folding, and ironing clothes. His work addresses the fundamental challenges posed by fabrics’ deformability and self-occlusions, focusing on perception and control. De Gusseme’s major contributions include pioneering the use of synthetic data to train convolutional neural networks for detecting semantic keypoints on cloth, enabling robust folding without requiring a full state estimate. His 2024 paper, “Learning Keypoints for Robotic Cloth Manipulation Using Synthetic Data,” has already garnered 14 citations, reflecting its impact on bridging the sim-to-real gap. He also developed a modular piezoresistive smart textile for state estimation and proposed a simplified two-parameter trajectory search space for effective folding in simulation. Notably, De Gusseme’s system won the folding track at the IROS 2022 Cloth Manipulation and Perception Competition, and he co-organized the Robotic Grasping and Manipulation Competition at ICRA 2024. His work, combining deep learning, simulation, and hardware innovation, is paving the way for practical, generalizable robotic cloth handling.
Research Focus
Key Achievements
Top Papers
- 1Learning Keypoints for Robotic Cloth Manipulation Using Synthetic Data14 citations · 2024
- 2Learning Keypoints from Synthetic Data for Robotic Cloth Folding8 citations · 2022
- 3Modular Piezoresistive Smart Textile for State Estimation of Cloths5 citations · 2021
- 4
- 5
- 6