The Breakdown Researchers used generative AI to turn text prompts into 3D-printed tactile graphics. Text2TactileGraphics creates raised shapes and textures to help convey visual information to users who are blind or have low vision. The research team tested the tool with participants from VisAbility Pittsburgh and the Library of Accessible Media for Pennsylvanians. * * [...]
The Breakdown: RIO lets researchers use the same software across different robots, reducing the need to rebuild code for each new platform. This functionality speeds up robot setup and lets researchers spend more time developing and testing robot behaviors. The system helps accelerate robotics research and real-world deployment. * * * Researchers set up [...]
The Breakdown : An algorithm driven by wearable sensors advances assistive feeding by predicting when someone is ready for their next bite. It helps robots adapt to real-world eating, including conversation and pauses. Adjustable settings let users set the pace while easing workload. * * * New work led by Carnegie Mellon University researchers could [...]
The Breakdown: iTagPDF automatically adds accessibility metadata to LaTeX-based PDFs. It combines visual layout analysis with original source document information. The system improves accuracy and reduces the need for manual tagging. * * * Researchers in the Carnegie Mellon University School of Computer Science have developed a system that automatically improves PDF accessibility. Although PDFs [...]
Steinfeld received the Test of Time Award on behalf of his team at the 2026 ACM/IEEE International Conference on Human-Robot Interaction in Edinburgh. A team led by Carnegie Mellon University’s Aaron Steinfeld has earned the inaugural Test of Time Award at the 2026 ACM/IEEE International Conference on Human-Robot Interaction (HRI). The award honors [...]
The Breakdown: A CMU study followed blind participants navigating a museum with a robotic guide. It revealed that navigation strategies shift from moment to moment in unpredictable environments. The findings highlight the need to design assistive technologies that adapt to users’ changing decisions in real time. * * * Assistive navigation robots are only as [...]
My life goal is to fulfill the science fiction vision of machines that achieve human levels of competence in perceiving, thinking, and acting. A more narrow technical goal is to understand how to get machines to generate and perceive human behavior. I use two complementary approaches, exploring humanoid robotics and human aware environments. Building humanoid [...]
The MattLab is developing the intelligence necessary to enable complex platforms to autonomously interact with and perform meaningful work in complex environments. The task areas include biologically inspired dynamic locomotion and learning, compliant manipulation for agriculture and food preparation, managing uncertainty in human-robot interaction, and field-ready search and rescue robotics. The central ideas that drive [...]
The Momentum Lab focuses on advancing robotics research through innovative approaches to manipulation, learning, and human-robot interaction. Our research spans soft robotics, computer vision, machine learning, and multi-agent systems, with applications in healthcare, manufacturing, and everyday assistance.
From autonomous cars in cities to mobile manipulators at home, our lab aims to design robots that reliably interact with people. What makes this hard is that human behavior---especially when interacting with other agents---is vastly complex, varying between individuals, environments, and over time. Thus, robots rely on data and machine learning throughout the design process [...]
I am an Assistant Professor in the Robotics Institute at Carnegie Mellon University, leading the Interactive and Trustworthy Robotics Lab (Intent Lab). I'm broadly interested in enabling embodied AI agents to reliably interact with the open world. This includes---but is not limited to---quantifying a robot's confidence (e.g., in a requested task or in their predictive models [...]
For more information, please visit Laszlo Jeni's CUBE Lab Site.
We develop new computational, control, and sensing methods for robots to physically interact with and assist people. We bring together researchers that explore the intersection of physically assistive robotics, machine learning, physics simulation, perception, and human-robot interaction. Our research often has applications in healthcare robotics, including the advancement of robotic caregivers -- robots that assist [...]
My research broadly explores healthcare robotics, with an emphasis on empowering older adults and people with disabilities to live more independently and maintain a higher quality of life.My research lies at the intersection of physically assistive robotics, learning, physics simulation, haptic perception, and human-robot interaction.I am especially interested in physical human-robot interaction, and I focus on developing [...]
Our lab works to develop new methods for robot perception and control. We are focusing on deformable object manipulation, autonomous driving, and safe reinforcement learning.
About the TBD Lab We discover and examine new ways of supporting accessible transportation and human-robot interaction. This includes work on core issues in robotics and other computer science, like appropriate robot behaviors, trust and robot performance, and accessible interactions with AI and robots. Research Themes Most of the TBD Lab projects center on [...]
The Social Haptics, Robotics and Education Lab creates haptics and robotics to improve education and wellbeing For more details about projects, team and current openings visit the SHRED Lab Website.
The main theme of research in Bot Intelligence Group (BIG) is to develop robotic intelligence ranging from the low-level autonomy to the high-level cognitive abilities. We aim to develop robots that can cooperate or collaborate with humans in shared environments, learning to improve themselves over time through continual on- and off-line training, exploration, and interactions [...]
The Intelligent Control Lab focuses on building intelligent and autonomous robots that think, behave and interact with the world in the way that human beings do so that they can better serve, assist and collaborate with people in their daily lives across work, home and leisure. We are part of the Robotics Institute at Carnegie [...]
The goal of the Human And Robot Partners (HARP) lab is to understand and develop autonomous, intelligent robots that help people live better. Our robots engage people through social and physical interactions, monitoring human behavior to understand and predict the types of help people need. Our lab’s expertise includes robotics, human-robot interaction, machine learning, computer [...]
The ultimate goal of my research is to build intelligent and autonomous robots that think, behave and interact with the world in the way that human beings do, so that they can better serve, assist and collaborate with people in their daily lives across work, home and leisure. The fundamental research question is to ensure [...]
I am an Assistant Professor in the Robotics Institute at Carnegie Mellon University, where I lead the Human And Robot Partners (HARP) Lab. I'm interested in robotics, human-robot interaction, and assistive technology. My research focuses on developing intelligent, autonomous robots that help humans on complex tasks like eating a meal or learning a new skill. [...]
My research interests lie in the area of AI in robotics including autonomy, language understanding, multimodal perception, path planning, and machine learning. I am interested in creating persistent robots that can co-exist with humans in shared environments, learning to improve themselves over time through continuous training, exploration, and interactions. Toward this general goal, I am [...]
Research interests focus on developing reliable, highly autonomous systems (especially mobile robots) that operate in rich, uncertain environments. The goal is to create intelligent systems that can operate autonomously for long periods of time in unstructured, natural environments. This necessitates robots that can plan, effectively reason about uncertainty, diagnose and recover from unanticipated errors, reason [...]
The goal of the Human Sensing Lab is to develop new machine learning algorithms to model and understand human behavior from sensory data (e.g. video, motion capture, audio). Our work is motivated by applications in the fields of human health, biometrics and human-machine interface. For more information, visit the full lab site.
Agent Interoperability: We are designing reusable agent types, architectures, and languages to address the problem of interagent communication, coordination and negotiation. Electronic Commerce: We are addressing the need for agent-based negotiation and decision techniques that can be applied directly to the challenges facing the electronic marketplace. Information Gathering: The rapid growth of electronic information threatens [...]
The CREATE Lab is both a technology breeding ground and a community partner. It is this unique combination that enables a new form of local change: one that empowers the citizens to chart their technology future and, most important of all, their community's prospects for quality of life. Learn more on the CREATE Lab Website
Zakia Hammal is an Assistant Research Professor with the Robotics Institute in the School of Computer Science at Carnegie Mellon University. Dr. Hammal’s areas of expertise are multimodal human behavior modeling in social interaction, health informatics, and affective computing. Much of her recent work has addressed computational models for multimodal assessment of treatment outcomes in [...]
My research focuses on developing the intelligence necessary to enable complex platforms to autonomously interact with and perform meaningful work in complex environments. The task areas on which I am currently focusing include biologically inspired dynamic locomotion and learning, compliant manipulation for agriculture and food preparation, managing uncertainty in human-robot interaction, and field-ready search and [...]
Software agents and robots ranging from autonomous vehicles to intelligent assistants have become commonplace. We envision a future where this trend accelerates leading to large numbers of networked humans and robots working together for numerous applications ranging from manufacturing to environment exploration, crisis response and search and rescue. These multi-robot systems will be coordinating autonomously, [...]
My research interests focus on developing reliable, highly autonomous systems (especially mobile robots) that operate in rich, uncertain environments. The goal is to create intelligent systems that can operate autonomously for long periods of time in unstructured, natural environments. This necessitates robots that can plan, effectively reason about uncertainty, diagnose and recover from unanticipated errors, [...]
For more than ten years I have been exploring human-robot interaction with the aim of creating rich, effective and satisfying interactions between humans and robots. My research has focused specifically on human-robot collaboration, wherein the robotic and human agents in the system share the same unifying goal or utility function. I further sharpen my scope [...]
My current research effort focuses on three main areas, all involving the creation of innovative new hardware, software, and systems. The first area concerns distributed agent-based cooperative high-precision manipulation. The principal application is agile assembly of small high-precision electromechanical products such as computer storage devices, medical devices, communication devices, and other high-density mechatronic equipment. The [...]
