102 citations · 113 across the 15 of their papers we have counts for
15 papers
TACTIC: Understanding Tactile Encoders and Conditioning for Contact-rich Robot Manipulation Policies
Seongjin Bien, Débora Oliveira Makowski, Carlo Kneissl +6
Tactile information is essential for contact-rich manipulation tasks in robotics. Vision-based tactile sensors make it particularly easy to design end-to-end manipulation policies…
Norm2Tex: Augmenting Visuo-Tactile Simulations with Texture
Seongjin Bien, Débora Oliveira Makowski, Roberto Calandra +2
Large-scale datasets are essential for training generalist robot control policies. Collecting real-world tactile data is costly and time-consuming, motivating the use of tactile si…
SpikeDecoder: Realizing the GPT Architecture with Spiking Neural Networks
Claas Beger, Florian Walter, Alois Knoll
The Transformer architecture is widely regarded as the most powerful tool for natural language processing, but due to a high number of complex operations, it inherently faces the i…
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…
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…
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…
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…
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…
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…
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…
Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey
Ruiqi Zhang, Jing Hou, Florian Walter +7
Reinforcement Learning (RL) is a potent tool for sequential decision-making and has achieved performance surpassing human capabilities across many challenging real-world tasks. As…
A Review of Safe Reinforcement Learning: Methods, Theory and Applications
Shangding Gu, Long Yang, Yali Du +4
Reinforcement Learning (RL) has achieved tremendous success in many complex decision-making tasks. However, safety concerns are raised during deploying RL in real-world application…
Towards Cognitive Navigation: Design and Implementation of a Biologically Inspired Head Direction Cell Network
Zhenshan Bing, Amir EI Sewisy, Genghang Zhuang +4
As a vital cognitive function of animals, the navigation skill is first built on the accurate perception of the directional heading in the environment. Head direction cells (HDCs),…
Task-Independent Spiking Central Pattern Generator: A Learning-Based Approach
Elie Aljalbout, Florian Walter, Florian Röhrbein +1
Legged locomotion is a challenging task in the field of robotics but a rather simple one in nature. This motivates the use of biological methodologies as solutions to this problem.…