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20232026
most citedCloudTrack: Scalable UAV Tracking with Cloud Semantics

1 citations · 1 across the 5 of their papers we have counts for

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cs.RO2026

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…

cs.RO2025

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…

cs.RO2025

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.RO20241 cited

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.RO2023

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…