New research from CMU Robotics Institute Institute aims to increase autonomy for individuals with motor impairments by introducing a head-worn device that will help them control a mobile manipulator. bit.ly/3JgJNlV

Is your robot 🤖 safe around humans🚸? Or will it fail catastrophically🤕? Excited to introduce "Natural Adversarial Frontier", a framework for probing the robustness of Human-Robot Interactions. To appear at #CoRL2023 🧵(1/8) Joint work with Anca Dragan Daniel Brown

Can we eliminate human effort for reward engineering in RL? Introducing RL-VLM-F, which uses preference feedback from VLMs to automatically generate rewards to learn new tasks, using only a text description of the task and the agent's visual observations! arxiv.org/abs/2402.03681

How to build a safe, generalizable robot-assisted dressing system? Our #RAL2024 paper introduces a novel multi-modal learning method, combining a simulation-trained vision policy and a real-world-learned force dynamics model, with strong results in a 10-participant human study.🧵

CMU experts in human-robot interaction propose VoicePilot: a framework + design guidelines for incorporating LLMs as speech interfaces for physically assistive robots 🤖🦾 The paper was accepted at UIST 2024 - held in Pittsburgh this October! Read: ri.cmu.edu/voicepilot-fra…