1 citations · 2 across the 11 of their papers we have counts for
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KnowDemo: Knowledge-Guided Robot Demonstration Generation from Human Videos
Zhiyuan Gao, Yanxiang Zhan, Mohammad Khoshnazar +2
Learning robot manipulation policies typically requires substantial demonstration data, which are costly to collect on real robots. Recent methods generate robot demonstrations fro…
FOCAL-VLA: Subtask-Guided Geometry Distillation and Implicit World Modeling for Vision-Language-Action Models
Zhiyuan Gao, Di Wen, Yanxiang Zhan +4
Vision-language-action (VLA) models built on pretrained vision-language models have demonstrated strong performance across diverse robotic manipulation tasks. However, VLA models t…
Interventional Causal Circuits for Safe Robot Action Testing and Failure Recovery
Naren Vasantakumaar, Tom Schierenbeck, Michael Beetz
Safe physical AI for robot actions are required not only likely to succeed but tested to be safe before execution. In practice, however, formal testing of motion parameters is comp…
LLM-Guided Future Hypotheses for Horizon-Aware Exploration in Multi-Step Robot Manipulation
Mohammad Khoshnazar, Andrew Melnik, Michael Beetz
Multi-step robot manipulation requires acting under uncertainty about how the scene will evolve, making exploration and policy adaptation challenging. We study whether short-horizo…
Open, Reproducible and Trustworthy Robot-Based Experiments with Virtual Labs and Digital-Twin-Based Execution Tracing
Benjamin Alt, Mareike Picklum, Sorin Arion +2
We envision a future in which autonomous robots conduct scientific experiments in ways that are not only precise and repeatable, but also open, trustworthy, and transparent. To rea…
Grounding Language Models with Semantic Digital Twins for Robotic Planning
Mehreen Naeem, Andrew Melnik, Michael Beetz
We introduce a novel framework that integrates Semantic Digital Twins (SDTs) with Large Language Models (LLMs) to enable adaptive and goal-driven robotic task execution in dynamic…
Shadow Program Inversion with Differentiable Planning: A Framework for Unified Robot Program Parameter and Trajectory Optimization
Benjamin Alt, Claudius Kienle, Darko Katic +2
This paper presents SPI-DP, a novel first-order optimizer capable of optimizing robot programs with respect to both high-level task objectives and motion-level constraints. To that…
Human-AI Interaction in Industrial Robotics: Design and Empirical Evaluation of a User Interface for Explainable AI-Based Robot Program Optimization
Benjamin Alt, Johannes Zahn, Claudius Kienle +7
While recent advances in deep learning have demonstrated its transformative potential, its adoption for real-world manufacturing applications remains limited. We present an Explana…
BANSAI: Towards Bridging the AI Adoption Gap in Industrial Robotics with Neurosymbolic Programming
Benjamin Alt, Julia Dvorak, Darko Katic +3
Over the past decade, deep learning helped solve manipulation problems across all domains of robotics. At the same time, industrial robots continue to be programmed overwhelmingly…
RoboGrind: Intuitive and Interactive Surface Treatment with Industrial Robots
Benjamin Alt, Florian Stöckl, Silvan Müller +10
Surface treatment tasks such as grinding, sanding or polishing are a vital step of the value chain in many industries, but are notoriously challenging to automate. We present RoboG…