3 citations · 5 across the 6 of their papers we have counts for
6 papers
The Neural Compass: Probabilistic Relative Feature Fields for Robotic Search
Gabriele Somaschini, Adrian Röfer, Abhinav Valada
Object co-occurrences provide a key cue for finding objects successfully and efficiently in unfamiliar environments. Typically, one looks for cups in kitchens and views fridges as…
Preference-Based Long-Horizon Robotic Stacking with Multimodal Large Language Models
Wanming Yu, Adrian Röfer, Abhinav Valada +1
Pretrained large language models (LLMs) can work as high-level robotic planners by reasoning over abstract task descriptions and natural language instructions, etc. However, they h…
Articulated Object Estimation in the Wild
Abdelrhman Werby, Martin Büchner, Adrian Röfer +3
Understanding the 3D motion of articulated objects is essential in robotic scene understanding, mobile manipulation, and motion planning. Prior methods for articulation estimation…
Doing Right by Not Doing Wrong in Human-Robot Collaboration
Laura Londoño, Adrian Röfer, Tim Welschehold +1
As robotic systems become more and more capable of assisting humans in their everyday lives, we must consider the opportunities for these artificial agents to make their human coll…
Robot Skill Adaptation via Soft Actor-Critic Gaussian Mixture Models
Iman Nematollahi, Erick Rosete-Beas, Adrian Röfer +3
A core challenge for an autonomous agent acting in the real world is to adapt its repertoire of skills to cope with its noisy perception and dynamics. To scale learning of skills t…
Semantic Linking Maps for Active Visual Object Search
Zhen Zeng, Adrian Röfer, Odest Chadwicke Jenkins
We aim for mobile robots to function in a variety of common human environments. Such robots need to be able to reason about the locations of previously unseen target objects. Landm…