5 papers
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…
Closing the Loop in Teleoperation: Episode-Level Data Quality Assessment and Feedback for High-Quality Demonstration Collection
Gokul Narayanan, Yash Shahapurkar, Melih Erdogan +2
Industrial automation is at a pivotal moment, as Physical AI is driving a transition from rigid, hand-engineered automation systems toward more flexible and adaptive systems. This…
SheetMind: An End-to-End LLM-Powered Multi-Agent Framework for Spreadsheet Automation
Xi Cheng, Ruiyan Zhu, Ke Liu +8
We present SheetMind, a modular multi-agent framework powered by large language models (LLMs) for spreadsheet automation via natural language instructions. In this paper, we introd…
PogoDrone: Design, Model, and Control of a Jumping Quadrotor
Brian Zhu, Jiawei Xu, Andrew Charway +1
We present a design, model, and control for a novel jumping-flying robot that is called PogoDrone. The robot is composed of a quadrotor with a passive mechanism for jumping. The ro…