6 papers
Learning to Localize Reference Trajectories in Image-Space for Visual Navigation
Finn Lukas Busch, Matti Vahs, Quantao Yang +4
We present LoTIS, a model for visual navigation that provides robot-agnostic image-space guidance by localizing a reference RGB trajectory in the robot's current view, without requ…
FUS3DMaps: Scalable and Accurate Open-Vocabulary Semantic Mapping by 3D Fusion of Voxel- and Instance-Level Layers
Timon Homberger, Finn Lukas Busch, Jesús Gerardo Ortega Peimbert +2
Open-vocabulary semantic mapping enables robots to spatially ground previously unseen concepts without requiring predefined class sets. Current training-free methods commonly rely…
DIV-Nav: Open-Vocabulary Spatial Relationships for Multi-Object Navigation
Jesús Ortega-Peimbert, Finn Lukas Busch, Timon Homberger +2
Advances in open-vocabulary semantic mapping and object navigation have enabled robots to perform an informed search of their environment for an arbitrary object. However, such zer…
The First WARA Robotics Mobile Manipulation Challenge -- Lessons Learned
David Cáceres DomÃnguez, Marco Iannotta, Abhishek Kashyap +21
The first WARA Robotics Mobile Manipulation Challenge, held in December 2024 at ABB Corporate Research in VästerÃ¥s, Sweden, addressed the automation of task-intensive and repetit…
FLoRA: Sample-Efficient Preference-based RL via Low-Rank Style Adaptation of Reward Functions
Daniel Marta, Simon Holk, Miguel Vasco +6
Preference-based reinforcement learning (PbRL) is a suitable approach for style adaptation of pre-trained robotic behavior: adapting the robot's policy to follow human user prefere…
One Map to Find Them All: Real-time Open-Vocabulary Mapping for Zero-shot Multi-Object Navigation
Finn Lukas Busch, Timon Homberger, Jesús Ortega-Peimbert +2
The capability to efficiently search for objects in complex environments is fundamental for many real-world robot applications. Recent advances in open-vocabulary vision models hav…