1 citations · 1 across the 4 of their papers we have counts for
4 papers · 2 filters
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…
Learning to Act While Waiting: RL Finetuning of Generalist Robot Policies Under Inference Latency
Brian Zhu, Momen Khalil, E Harrison +17
While reinforcement learning (RL) allows generalist robot policies to continually improve during deployment, the large model size of modern generalist policies, such as VLAs, poses…
A Factory-Floor Deployment Case Study of VLA Pipelines for Industrial Packaging Task: Workflow, Failures, and Lessons
Brian Zhu, Philipp Schmitt, Philine Meister +12
Vision-Language-Action (VLA) policies have shown promising manipulation capabilities, yet their practical impact is often limited by the reliability demands of real-world deploymen…
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…