21 citations · 22 across the 21 of their papers we have counts for
22 papers
Wrench-ACT: Enhancing Robot Policies for Contact Rich Behavior Using Direct Wrench Control
Johannes Hechtl, Yannik Blei, Simon Ball +5
While contact-rich manipulation requires deliberate regulation of interaction forces, recent approaches to robot manipulation learning predominantly represent actions as target pos…
What do VLM-Based Vision-Language Navigation Models Rely on: Interpreting and Steering Policy Behavior
Débora Oliveira Makowski, Samiran Gode, Abhijeet Nayak +4
Modern Vision-Language Navigation (VLN) models rely mostly on pre-trained large Vision-Language Models (VLMs) to predict navigation actions. While this fusion of language instructi…
Adaptive World Memory 3D Foundation Model for Scalable 3D Mapping, Localization, and Rendering
Tianchen Deng, Guole Shen, Yilin Shen +7
Recent 3D foundation models enable generalizable geometric reasoning from RGB images but remain limited in persistent memory, scalability, and renderable scene modeling. We present…
DUET-DINO: Simultaneous Cross-View World Modeling for Latent Planning in Robot Manipulation
Nisarga Nilavadi, Ralf Römer, Moritz Reuss +5
Action-conditioned latent world models predict future visual representations, enabling zero-shot goal-conditioned robot planning and control. However, their predictions for fine-gr…
Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents
Suman Navaratnarajah, Taehyoung Kim, Jona Ruthardt +5
Multimodal Large Language Models (MLLMs) are emerging as core reasoning modules for embodied agents, yet it remains unclear how well general-purpose models can solve long-horizon e…
DuoBench: A Reproducible Benchmark for Bimanual Manipulation in Simulation and the Real World
Tobias Jülg, Seongjin Bien, Simon Hilber +7
Bimanual robot systems substantially expand manipulation capabilities, but coordinating two arms introduces additional control complexity and failure modes that are not well captur…
Shape Formation for the Cooperative Transportation of Arbitrary Objects Using Multi-Agent Reinforcement Learning
Mohamed Sayed, Wolfram Burgard, Tanja Katharina Kaiser
Cooperative object transportation is essential in numerous domains, including industrial to domestic services. A popular transportation strategy is to carry objects on top of multi…
OGScene3D: Incremental Open-Vocabulary 3D Gaussian Scene Graph Mapping for Scene Understanding
Siting Zhu, Ziyun Lu, Guangming Wang +5
Open-vocabulary scene understanding is crucial for robotic applications, enabling robots to comprehend complex 3D environmental contexts and supporting various downstream tasks suc…
Rewarding DINO: Predicting Dense Rewards with Vision Foundation Models
Pierre Krack, Tobias Jülg, Wolfram Burgard +1
Well-designed dense reward functions in robot manipulation not only indicate whether a task is completed but also encode progress along the way. Generally, designing dense rewards…
Enabling Dynamic Tracking in Vision-Language-Action Models via Time-Discrete and Time-Continuous Velocity Feedforward
Johannes Hechtl, Philipp Schmitt, Georg von Wichert +1
While vision-language-action (VLA) models have shown great promise for robot manipulation, their deployment on rigid industrial robots remains challenging due to the inherent trade…
VLAgents: A Policy Server for Efficient VLA Inference
Tobias Jülg, Khaled Gamal, Nisarga Nilavadi +5
The rapid emergence of Vision-Language-Action models (VLAs) has a significant impact on robotics. However, their deployment remains complex due to the fragmented interfaces and the…
ConPoSe: LLM-Guided Contact Point Selection for Scalable Cooperative Object Pushing
Noah Steinkrüger, Nisarga Nilavadi, Wolfram Burgard +1
Object transportation in cluttered environments is a fundamental task in various domains, including domestic service and warehouse logistics. In cooperative object transport, multi…
Robot Control Stack: A Lean Ecosystem for Robot Learning at Scale
Tobias Jülg, Pierre Krack, Seongjin Bien +7
Vision-Language-Action models (VLAs) mark a major shift in robot learning. They replace specialized architectures and task-tailored components of expert policies with large-scale d…
MetricNet: Recovering Metric Scale in Generative Navigation Policies
Abhijeet Nayak, Débora Oliveira Makowski, Samiran Gode +2
Generative navigation policies have made rapid progress in improving end-to-end learned navigation. Despite their promising results, this paradigm has two structural problems. Firs…
A roadmap for AI in robotics
Aude Billard, Alin Albu-Schaeffer, Michael Beetz +8
AI technologies, including deep learning, large-language models have gone from one breakthrough to the other. As a result, we are witnessing growing excitement in robotics at the p…
Augmented Reality for RObots (ARRO): Pointing Visuomotor Policies Towards Visual Robustness
Reihaneh Mirjalili, Tobias Jülg, Florian Walter +1
Visuomotor policies trained on human expert demonstrations have recently shown strong performance across a wide range of robotic manipulation tasks. However, these policies remain…
iPack: Intuitive Bin Packing with Large Language Models
Yannik Blei, Michael Krawez, Adrian Göß +5
Robotics and automation are increasingly influential in logistics but remain largely confined to traditional warehouses. In grocery retail, advancements such as cashier-less superm…
REGRACE: A Robust and Efficient Graph-based Re-localization Algorithm using Consistency Evaluation
Débora N. P. Oliveira, Joshua Knights, Sebastián Barbas Laina +3
Loop closures are essential for correcting odometry drift and creating consistent maps, especially in the context of large-scale navigation. Current methods using dense point cloud…
FlowNav: Combining Flow Matching and Depth Priors for Efficient Navigation
Samiran Gode, Abhijeet Nayak, Débora N. P. Oliveira +3
Effective robot navigation in unseen environments is a challenging task that requires precise control actions at high frequencies. Recent advances have framed it as an image-goal-c…
Did You Hear That? Introducing AADG: A Framework for Generating Benchmark Data in Audio Anomaly Detection
Ksheeraja Raghavan, Samiran Gode, Ankit Shah +4
We introduce a novel, general-purpose audio generation framework specifically designed for anomaly detection and localization. Unlike existing datasets that predominantly focus on…
VLM-Vac: Enhancing Smart Vacuums through VLM Knowledge Distillation and Language-Guided Experience Replay
Reihaneh Mirjalili, Michael Krawez, Florian Walter +1
In this paper, we propose VLM-Vac, a novel framework designed to enhance the autonomy of smart robot vacuum cleaners. Our approach integrates the zero-shot object detection capabil…
CloudTrack: Scalable UAV Tracking with Cloud Semantics
Yannik Blei, Michael Krawez, Nisarga Nilavadi +2
Nowadays, unmanned aerial vehicles (UAVs) are commonly used in search and rescue scenarios to gather information in the search area. The automatic identification of the person sear…