At the HIRO Group, we perform research at the intersection human-robot interaction, artificial intelligence, and robot control & planning with the goal of developing robot technologies that enable close, natural, and extended cooperation with humans. Our research effort is divided in three, partially overlapping, tightly coupled subteams. They are highlighted below.
Control and Artificial Skin
Point of Contact: Caleb Escobedo, Mary West, Nataliya Nechyporenko
In this subteam, we focus on ensuring that humans and robots can interact safely by simultaneously developing novel sensing hardware and motion control frameworks. The hardware component of this project has led to the development of modular sensor units that can be positioned anywhere on the surface of a robot manipulator to gather information about the robot’s immediate surroundings. Using the information provided by our sensor units, we have developed a control framework that allows robot manipulators to anticipate, detect, and react to external contact that could otherwise be harmful. [Read More]
Learning, Modeling, and Robotics
Point of Contact: Joewie J. Koh, Anuj Pasricha, Stéphane Aroca-Ouellette, Gilberto Briscoe-Martinez, Ava Abderezaei, Srikrishna Bangalore Raghu, Chi-Hui Lin
Our team aims to advance fundamental robot capabilities for future human-robot scenarios. We develop sophisticated robot technologies for human environments, and address challenges in: multimodal motion planning, long-term robot autonomy, non-prehensile manipulation, natural language grounding, and cooperative multi-agent reinforcement learning. Through these initiatives, we work towards bridging the gap between robotics and artificial intelligence, pushing the boundaries of robotic abilities to improve thir real-world usefulness. [Read More]
Algorithmic HRI and Human-AI Teaming
Point of Contact: Kaleb Bishop, Clare Lohrmann, Yi-Shiuan Tung, Stéphane Aroca-Ouellette
The goal of this subteam is to create robot behaviors that make robots more effective teammates and collaborators with humans. We use an interdisciplinary approach, leveraging machine learning, cognitive science, and social psychology to make robots more predictable, legible, and safe around humans. This subteam works with a variety of collaborators to conduct foundational research and run human-subjects studies in-person, online, and in virtual reality to validate these approaches. [Read More]