103 citations · 154 across the 22 of their papers we have counts for
23 papers
MapDreamer: Aerial Imagery Conditioned Latent Diffusion for Lane-Level Map Generation
Julian Brandes, Philipp Crocoll, Wolfram Burgard
High definition map generation is essential for autonomous driving, yet remains a labor-intensive process at scale. We present MapDreamer, a generative diffusion model that synthes…
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…
DiWA: Diffusion Policy Adaptation with World Models
Akshay L Chandra, Iman Nematollahi, Chenguang Huang +3
Fine-tuning diffusion policies with reinforcement learning (RL) presents significant challenges. The long denoising sequence for each action prediction impedes effective reward pro…
Multimodal Spatial Language Maps for Robot Navigation and Manipulation
Chenguang Huang, Oier Mees, Andy Zeng +1
Grounding language to a navigating agent's observations can leverage pretrained multimodal foundation models to match perceptions to object or event descriptions. However, previous…
LUMOS: Language-Conditioned Imitation Learning with World Models
Iman Nematollahi, Branton DeMoss, Akshay L Chandra +3
We introduce LUMOS, a language-conditioned multi-task imitation learning framework for robotics. LUMOS learns skills by practicing them over many long-horizon rollouts in the laten…
Refined Policy Distillation: From VLA Generalists to RL Experts
Tobias Jülg, Wolfram Burgard, Florian Walter
Vision-Language-Action Models (VLAs) have demonstrated remarkable generalization capabilities in real-world experiments. However, their success rates are often not on par with expe…
Label-Efficient LiDAR Panoptic Segmentation
Ahmet Selim Çanakçı, Niclas Vödisch, Kürsat Petek +2
A main bottleneck of learning-based robotic scene understanding methods is the heavy reliance on extensive annotated training data, which often limits their generalization ability.…
LiDAR Registration with Visual Foundation Models
Niclas Vödisch, Giovanni Cioffi, Marco Cannici +2
LiDAR registration is a fundamental task in robotic mapping and localization. A critical component of aligning two point clouds is identifying robust point correspondences using po…
RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
Charles Xu, Qiyang Li, Jianlan Luo +1
Recent advances in robotic foundation models have enabled the development of generalist policies that can adapt to diverse tasks. While these models show impressive flexibility, th…
BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding
Chenguang Huang, Shengchao Yan, Wolfram Burgard
Dynamic scene understanding remains a persistent challenge in robotic applications. Early dynamic mapping methods focused on mitigating the negative influence of short-term dynamic…
Perception Matters: Enhancing Embodied AI with Uncertainty-Aware Semantic Segmentation
Sai Prasanna, Daniel Honerkamp, Kshitij Sirohi +3
Embodied AI has made significant progress acting in unexplored environments. However, tasks such as object search have largely focused on efficient policy learning. In this work, w…
Improving Out-of-Distribution Generalization of Trajectory Prediction for Autonomous Driving via Polynomial Representations
Yue Yao, Shengchao Yan, Daniel Goehring +2
Robustness against Out-of-Distribution (OoD) samples is a key performance indicator of a trajectory prediction model. However, the development and ranking of state-of-the-art (SotA…
LetsMap: Unsupervised Representation Learning for Semantic BEV Mapping
Nikhil Gosala, Kürsat Petek, B Ravi Kiran +4
Semantic Bird's Eye View (BEV) maps offer a rich representation with strong occlusion reasoning for various decision making tasks in autonomous driving. However, most BEV mapping a…
A Good Foundation is Worth Many Labels: Label-Efficient Panoptic Segmentation
Niclas Vödisch, Kürsat Petek, Markus Käppeler +2
A key challenge for the widespread application of learning-based models for robotic perception is to significantly reduce the required amount of annotated training data while achie…
Automatic Target-Less Camera-LiDAR Calibration From Motion and Deep Point Correspondences
Kürsat Petek, Niclas Vödisch, Johannes Meyer +3
Sensor setups of robotic platforms commonly include both camera and LiDAR as they provide complementary information. However, fusing these two modalities typically requires a highl…
uPLAM: Robust Panoptic Localization and Mapping Leveraging Perception Uncertainties
Kshitij Sirohi, Daniel Büscher, Wolfram Burgard
The availability of a robust map-based localization system is essential for the operation of many autonomously navigating vehicles. Since uncertainty is an inevitable part of perce…
Hierarchical Open-Vocabulary 3D Scene Graphs for Language-Grounded Robot Navigation
Abdelrhman Werby, Chenguang Huang, Martin Büchner +2
Recent open-vocabulary robot mapping methods enrich dense geometric maps with pre-trained visual-language features. While these maps allow for the prediction of point-wise saliency…
Bayesian Optimization for Sample-Efficient Policy Improvement in Robotic Manipulation
Adrian Röfer, Iman Nematollahi, Tim Welschehold +2
Sample efficient learning of manipulation skills poses a major challenge in robotics. While recent approaches demonstrate impressive advances in the type of task that can be addres…
Agent-Agnostic Centralized Training for Decentralized Multi-Agent Cooperative Driving
Shengchao Yan, Lukas König, Wolfram Burgard
Active traffic management with autonomous vehicles offers the potential for reduced congestion and improved traffic flow. However, developing effective algorithms for real-world sc…
BEVCar: Camera-Radar Fusion for BEV Map and Object Segmentation
Jonas Schramm, Niclas Vödisch, Kürsat Petek +4
Semantic scene segmentation from a bird's-eye-view (BEV) perspective plays a crucial role in facilitating planning and decision-making for mobile robots. Although recent vision-onl…
Evaluation of a Smart Mobile Robotic System for Industrial Plant Inspection and Supervision
Georg K. J. Fischer, Max Bergau, D. Adriana Gómez-Rosal +10
Automated and autonomous industrial inspection is a longstanding research field, driven by the necessity to enhance safety and efficiency within industrial settings. In addressing…
CenterGrasp: Object-Aware Implicit Representation Learning for Simultaneous Shape Reconstruction and 6-DoF Grasp Estimation
Eugenio Chisari, Nick Heppert, Tim Welschehold +2
Reliable object grasping is a crucial capability for autonomous robots. However, many existing grasping approaches focus on general clutter removal without explicitly modeling obje…
Robot Skill Generalization via Keypoint Integrated Soft Actor-Critic Gaussian Mixture Models
Iman Nematollahi, Kirill Yankov, Wolfram Burgard +1
A long-standing challenge for a robotic manipulation system operating in real-world scenarios is adapting and generalizing its acquired motor skills to unseen environments. We tack…