Search Results - "Mees, Oier"

What Matters in Language Conditioned Robotic Imitation Learning Over Unstructured Data by Mees, Oier, Hermann, Lukas, Burgard, Wolfram

“…A long-standing goal in robotics is to build robots that can perform a wide range of daily tasks from perceptions obtained with their onboard sensors and…”
Get full text

Choosing smartly: Adaptive multimodal fusion for object detection in changing environments by Mees, Oier, Eitel, Andreas, Burgard, Wolfram

“…Object detection is an essential task for autonomous robots operating in dynamic and changing environments. A robot should be able to detect objects in the…”
Get full text

Visual Language Maps for Robot Navigation by Huang, Chenguang, Mees, Oier, Zeng, Andy, Burgard, Wolfram

“…Grounding language to the visual observations of a navigating agent can be performed using off-the-shelf visual-language models pretrained on Internet-scale…”
Get full text

CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks by Mees, Oier, Hermann, Lukas, Rosete-Beas, Erick, Burgard, Wolfram Burgard

“…General-purpose robots coexisting with humans in their environment must learn to relate human language to their perceptions and actions to be useful in a range…”
Get full text

Self-supervised 3D Shape and Viewpoint Estimation from Single Images for Robotics by Mees, Oier, Tatarchenko, Maxim, Brox, Thomas, Burgard, Wolfram

“…We present a convolutional neural network for joint 3D shape prediction and viewpoint estimation from a single input image. During training, our network gets…”
Get full text

Hindsight for Foresight: Unsupervised Structured Dynamics Models from Physical Interaction by Nematollahi, Iman, Mees, Oier, Hermann, Lukas, Burgard, Wolfram

“…A key challenge for an agent learning to interact with the world is to reason about physical properties of objects and to foresee their dynamics under the…”
Get full text

Metric learning for generalizing spatial relations to new objects by Mees, Oier, Abdo, Nichola, Mazuran, Mladen, Burgard, Wolfram

“…Human-centered environments are rich with a wide variety of spatial relations between everyday objects. For autonomous robots to operate effectively in such…”
Get full text

Grounding Language with Visual Affordances over Unstructured Data by Mees, Oier, Borja-Diaz, Jessica, Burgard, Wolfram

“…Recent works have shown that Large Language Models (LLMs) can be applied to ground natural language to a wide variety of robot skills. However, in practice,…”
Get full text

Composing Pick-and-Place Tasks By Grounding Language by Mees, Oier, Burgard, Wolfram

“…Controlling robots to perform tasks via natural language is one of the most challenging topics in human-robot interaction. In this work, we present a robot…”
Get full text

Steering Your Generalists: Improving Robotic Foundation Models via Value Guidance by Nakamoto, Mitsuhiko, Mees, Oier, Kumar, Aviral, Levine, Sergey

“…Large, general-purpose robotic policies trained on diverse demonstration datasets have been shown to be remarkably effective both for controlling a variety of…”
Get full text

Scaling Cross-Embodied Learning: One Policy for Manipulation, Navigation, Locomotion and Aviation by Doshi, Ria, Walke, Homer, Mees, Oier, Dasari, Sudeep, Levine, Sergey

“…Modern machine learning systems rely on large datasets to attain broad generalization, and this often poses a challenge in robot learning, where each robotic…”
Get full text

Grounding Language with Visual Affordances over Unstructured Data by Mees, Oier, Borja-Diaz, Jessica, Burgard, Wolfram

“…Recent works have shown that Large Language Models (LLMs) can be applied to ground natural language to a wide variety of robot skills. However, in practice,…”
Get full text

Vision-Language Models Provide Promptable Representations for Reinforcement Learning by Chen, William, Mees, Oier, Kumar, Aviral, Levine, Sergey

“…Humans can quickly learn new behaviors by leveraging background world knowledge. In contrast, agents trained with reinforcement learning (RL) typically learn…”
Get full text

What Matters in Language Conditioned Robotic Imitation Learning over Unstructured Data by Mees, Oier, Hermann, Lukas, Burgard, Wolfram

“…A long-standing goal in robotics is to build robots that can perform a wide range of daily tasks from perceptions obtained with their onboard sensors and…”
Get full text

Audio Visual Language Maps for Robot Navigation by Huang, Chenguang, Mees, Oier, Zeng, Andy, Burgard, Wolfram

“…While interacting in the world is a multi-sensory experience, many robots continue to predominantly rely on visual perception to map and navigate in their…”
Get full text

Scaling Robot Policy Learning via Zero-Shot Labeling with Foundation Models by Blank, Nils, Reuss, Moritz, Rühle, Marcel, Yağmurlu, Ömer Erdinç, Wenzel, Fabian, Mees, Oier, Lioutikov, Rudolf

“…A central challenge towards developing robots that can relate human language to their perception and actions is the scarcity of natural language annotations in…”
Get full text

The Ingredients for Robotic Diffusion Transformers by Dasari, Sudeep, Mees, Oier, Zhao, Sebastian, Srirama, Mohan Kumar, Levine, Sergey

“…In recent years roboticists have achieved remarkable progress in solving increasingly general tasks on dexterous robotic hardware by leveraging high capacity…”
Get full text

LeLaN: Learning A Language-Conditioned Navigation Policy from In-the-Wild Videos by Hirose, Noriaki, Glossop, Catherine, Sridhar, Ajay, Shah, Dhruv, Mees, Oier, Levine, Sergey

“…The world is filled with a wide variety of objects. For robots to be useful, they need the ability to find arbitrary objects described by people. In this…”
Get full text

Policy Adaptation via Language Optimization: Decomposing Tasks for Few-Shot Imitation by Myers, Vivek, Zheng, Bill Chunyuan, Mees, Oier, Levine, Sergey, Fang, Kuan

“…Learned language-conditioned robot policies often struggle to effectively adapt to new real-world tasks even when pre-trained across a diverse set of…”
Get full text

Autonomous Improvement of Instruction Following Skills via Foundation Models by Zhou, Zhiyuan, Atreya, Pranav, Lee, Abraham, Walke, Homer, Mees, Oier, Levine, Sergey

“…Intelligent instruction-following robots capable of improving from autonomously collected experience have the potential to transform robot learning: instead of…”
Get full text