7 papers
Which objects help me to act effectively? Reasoning about physically-grounded affordances
Anne Kemmeren, Gertjan Burghouts, Michael van Bekkum +2
For effective interactions with the open world, robots should understand how interactions with known and novel objects help them towards their goal. A key aspect of this understand…
Lightweight Uncertainty Quantification with Simplex Semantic Segmentation for Terrain Traversability
Judith Dijk, Gertjan Burghouts, Kapil D. Katyal +5
For navigation of robots, image segmentation is an important component to determining a terrain's traversability. For safe and efficient navigation, it is key to assess the uncerta…
Open-World Visual Reasoning by a Neuro-Symbolic Program of Zero-Shot Symbols
Gertjan Burghouts, Fieke Hillerström, Erwin Walraven +5
We consider the problem of finding spatial configurations of multiple objects in images, e.g., a mobile inspection robot is tasked to localize abandoned tools on the floor. We defi…
Affordance Perception by a Knowledge-Guided Vision-Language Model with Efficient Error Correction
Gertjan Burghouts, Marianne Schaaphok, Michael van Bekkum +3
Mobile robot platforms will increasingly be tasked with activities that involve grasping and manipulating objects in open world environments. Affordance understanding provides a ro…
Scaling 3D Reasoning with LMMs to Large Robot Mission Environments Using Datagraphs
W. J. Meijer, A. C. Kemmeren, E. H. J. Riemens +4
This paper addresses the challenge of scaling Large Multimodal Models (LMMs) to expansive 3D environments. Solving this open problem is especially relevant for robot deployment in…
Language-Based Augmentation to Address Shortcut Learning in Object Goal Navigation
Dennis Hoftijzer, Gertjan Burghouts, Luuk Spreeuwers
Deep Reinforcement Learning (DRL) has shown great potential in enabling robots to find certain objects (e.g., `find a fridge') in environments like homes or schools. This task is k…