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cs.RO2026

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…

cs.RO20265 cited

Lan-grasp: Using Large Language Models for Semantic Object Grasping and Placement

Reihaneh Mirjalili, Michael Krawez, Yannik Blei +3

In this paper, we propose Lan-grasp, a novel approach towards more appropriate semantic grasping and placing. We leverage foundation models to equip the robot with a semantic under…

cs.RO2026

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…

cs.RO2025

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…

cs.RO2025

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…

cs.RO2024

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…