The Breakdown Malfunctioning humanoids can hurt people, and improved safety measures are essential as these robots become more common in daily life. CMU and Siemens partnered to create a method to determine the "safe stoppability" of humanoids. They also defined conditions where it's safe to stop a humanoid using simulation, resulting in Proactive Refinement of [...]
The Breakdown: LAMP helps multiple robots collaborate to move objects. The system enables the robots to navigate crowded spaces and coordinate their movements. It could allow for more efficient workflows in warehouses and other complex environments. * * * Jiaoyang Li (left) and Shuai Zhou (right) are developing LAMP, a system that helps teams [...]
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: VideoManip teaches robots manipulation skills using videos of people interacting with objects. It reconstructs movements and estimates how people make contact with objects. The system helps robots learn new skills without time-consuming, human-operated demonstrations. * * * Researchers in Carnegie Mellon University's School of Computer Science are developing a new way for robots [...]
A research group at Carnegie Mellon University’s Robotics Institute (RI) will host the latest phase of the Vision-Language-Navigation (VLN) Challenge, bringing researchers together to enable robots to understand and act on human instructions in the real world — one of robotics’ most famously difficult pursuits. This year’s challenge pushes beyond earlier versions by removing “ground [...]
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 [...]
A new report from Carnegie Mellon University’s CREATE Lab examines how steelmaking influences economic opportunity and environmental conditions in southwestern Pennsylvania. The report combines employment and demographic data with advanced air pollution modeling to analyze how employment at steelmaking facilities aligns with long-term economic conditions in the Mon Valley, a group of municipalities along the [...]
I’m interested in things that move. My goal is to enable robotic systems that can match or exceed the level of agility, efficiency, and robustness demonstrated by humans and animals, especially in challenging environments. One focus of my research is building on ideas from control, estimation, game theory, optimization, and physics to develop new algorithms. [...]
Aditya Sripada (left) and Abhishek Warrier (right) Curiosity allows humans to pull ideas from fiction and give life to them in the real world. For Carnegie Mellon University alumni Aditya Sripada and Abhishek Warrier, a question inspired by a fictional robot in the film "Interstellar" served as the impetus for building, testing and [...]
The Breakdown: A caregiving robot that responds to spoken instructions while performing physical tasks may make robots easier to use and understand. The robot explains its actions, listens to feedback and adjusts in real time. CMU researchers tested the robot with residents at an independent living facility. *** Residents at Baptist Senior Family's Providence Point, [...]
The Breakdown The BFM-Zero system lets humanoid robots switch seamlessly between many skills. It relies on unsupervised reinforcement learning, allowing robots to explore, generalize and self-improve. The system moves robotics closer to general-purpose humanoids that can adapt safely in everyday environments. *** Humanoid robots in a lab at Carnegie Mellon University don't fall over when [...]
Robots took to the runway — strutting, spinning and dancing — in a fashion show that brought art and engineering together to rethink how humans and machines might coexist. Draped in metallic fabric and sculptural garments, the robots appeared alongside human partners in a rare performance that blended engineering with artistic expression. The robot fashion [...]
The quadruped robots explore grass terrain at night. Team Chiron, a group of researchers from Carnegie Mellon University and the University of Pittsburgh, will compete in the third and final phase of the DARPA Triage Challenge (DTC) next November. The DTC seeks to develop portable, autonomous systems that can assess and monitor injured [...]
Rumaisa Azeem and Andrew Hundt, co-first authors of the paper. The Breakdown: Robots powered by popular AI models failed multiple safety and discrimination tests. The tests revealed deeper risks, including bias and unsafe physical behavior. The researchers call for regular risk assessments before AI systems control real-world robots. *** Robots powered by popular [...]
The Breakdown SPOT helps robots understand their surroundings using 3D camera data. The system assists robots as they determine what objects to move and where to place them to reach a goal. SPOT enables intuitive, goal-driven robotic planning similar to how humans organize or clean a space. *** Researchers at Carnegie Mellon University’s Robotics Institute [...]
Appleseed Labs, a team within the Kantor Lab at Carnegie Mellon University, received the Excellence in Regenerative Agriculture award at the 2025 Farm Robotics Challenge. The team was advised by Senior Project Scientist Francisco Yandun and included students Will Heitman, Joyce Zhu, Ken Muangsiri, Alex Smith, Qimeng Yu and Rohan Walia, who joined from the [...]
Vivian Shen, Robotics Institute Ph.D. student, emerged as the champion of the Carnegie Mellon University Three Minute Thesis competition (3MT). The internationally recognized competition, hosted by Carnegie Mellon Libraries, challenges Ph.D. students from across the university to present their thesis in an accessible language in just three minutes. 3MT offers CMU doctoral candidates of any [...]
Researchers from the Resilient Intelligent Systems Lab (RISLab) at the Carnegie Mellon University Robotics Institute and the National Robotics and Engineering Center (NREC) have received the Best Paper Award at the IEEE Symposium on Safety, Security, and Rescue Robotics (SSRR) 2024 for their work titled Rapid quadrotor navigation in diverse environments using an onboard depth camera. SSRR hosts [...]
The framework allows the robot to create photorealistic scene representations in low-light environments. Robots lift heavy loads in warehouses, deliver meals to diners, and even tackle housework. However, a lot of robotic work goes unseen – quite literally. Robots and autonomous vehicles are routinely deployed for critical tasks such as exploration, inspection, transportation, [...]
Our group is dedicated to pioneering cutting-edge wearables, robotics, and AI technologies that transcend traditional human physical capabilities, aiming to redefine the boundaries of human mobility. At Carnegie Mellon University’s MetaMobility Lab, led by Dr. Inseung Kang, our focus is on advancing wearable assistive technologies, such as robotic exoskeletons, to enhance human mobility. Our interdisciplinary [...]
The DRIVE Lab performs research on behaviors, planning, control, and perception for autonomous vehicles. Its emphases include socially cooperative autonomous driving, safe control under uncertainty, high-performance driving for autonomous racing, and adaptation to dynamic environments. Adversarial Multi-Agent Systems We want to enable robots to operate safely and optimally in the presence of adverserial agents. Our [...]
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 Legged Systems Group is engaged in research on dynamics, control and learning of human locomotion and related applications in rehabilitation robotics. Our group combines physics, biomechanics and neuroscience with control theory and machine learning to understand how the human system locomotes and to translate the resulting insights into functional lower-limb assistive robots. Our research [...]
Research focuses on developing fundamental algorithms that enable large teams of autonomous agents to accomplish collaborative tasks intelligently in dynamic environments. Applications of this research include mobile robot coordination for automated warehousing and, in general, nonholonomic robot teams, drone swarm control, multi-arm assembly, character control in video games, and traffic management for airports, railway networks, [...]
Cognitive Assistance is a new research agenda to assist everyday life by fully utilizing the power of AI. AI is now starting to understand the surrounding world to make sense of the information for people who are unable to see. Additionally, those computers are starting to remember everything to fulfill the declining cognitive abilities of [...]
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 [...]
The lab is run by Yonatan Bisk and is housed primarily in the Language Technologies Institute, but includes members from both the Machine Learning Department and the Robotics Institute.
My group’s research is on developing wearable assistive devices (e.g., robotic exoskeletons) that can augment human mobility during locomotion. Some research topics include: 1) Robotic exoskeleton design and control (mechatronic design) using wearable sensors and deep learning 2) Designing a foundational model for estimating user physiology for a robotic exoskeleton 3) Computer vision-based whole-body human [...]
The goal of the FARM Lab (formerly Kantor Lab) is to develop techniques for perceiving and manipulating plants using robots. The potential applications are broad, and include fruit detection and picking, yield prediction, health assessment, pruning, and crop management, among others. The lab currently has projects spanning outdoor interactions with field crops, indoor work with [...]
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 [...]
I am interested in planning, scheduling, optimization, and learning for large-scale multi-robot coordination. My research focuses on developing fundamental algorithms that enable large teams of autonomous agents to accomplish collaborative tasks intelligently in dynamic environments. Applications of my research include mobile robot coordination for automated warehousing and, in general, non-holonomic robot teams, drone swarm control, [...]
Please visit our lab site to learn more.
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.
I am an Assistant Professor in the Robotics Institute at Carnegie Mellon University, where I lead the Social Haptics Robotics and Education (SHRED) Laboratory. My research combines the areas of robotics, haptics, human-computer interaction, and education. My main areas of focus and interest are developing low-cost, open-source robotic technology for educational applications and understanding the [...]
Foam hands seek to bridge the gap in realized dexterity between soft robotics and classical rigid robot hands. Our philosophy is that this will come from an effective synergy of advances in materials and design, simulation and perception, and planning and control. The Foam Hand Lab brings together these disciplines to capitalize on the advantages [...]
Our primary focus is on multifunctional materials for soft robots that are safe for human interaction.
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 [...]
Carnegie Mellon has been a pioneering leader in autonomous transportation and self-driving technologies. The collaboration between CMU and Argo AI will continue to advance important research that will address the consequences of scaling technological innovation to society at large. This center will focus on fundamental research that will produce advanced perception and next-generation decision-making algorithms that enable vehicles to [...]
About The Carnegie Mellon Textiles Lab extends the state of the art in textile design and fabrication. We seek to collaborate broadly both inside and outside the Carnegie Mellon community. Our space in Wean 1334 houses a state-of-the art knitting machine, computer-controlled quilting machine, prosumer-level jacquard loom, and various small textiles fabrication tools and supplies. [...]
Research Topics Computer Vision Light-weight Deep Learning Visual Perception on Moving Platforms Wireless and Wearable Sensing Applications Computer Vision Surveillance & Security Field Robotics Health Care Advances in sensors, machine learning and computer vision hold tremendous potential to reshape our world. DeLight focuses on unlocking this potential contained in applied machine learning approaches, and applying [...]
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. [...]
I build creative tools -- software and hardware that help people make things. I am particularly interested in systems that operate in real-time and build user intuition. I’ve been applying these ideas to textiles fabrication and machine knitting as the leader of the Carnegie Mellon Textiles Lab; as well as to other domains including robotic [...]
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 [...]
My research interest is in end-to-end robotic systems tailored for complex outdoor environments, synthesizing cutting-edge research across various branches of robotics to address real-world challenges. This often leads to proof-of-concept robotic systems that demonstrate novel concepts to do things that have never been done before. My particular interest is in agriculture, where I'm fascinated not [...]
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.
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 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
The Robotics Academy is committed to using the motivational effects of robotics to excite students about science and technology. We are an educational outreach of Carnegie Mellon University, and part of the university's world-renowned Robotics Institute. Our administrative staff and development team are housed in the National Robotics Engineering Center (NREC), where robots for business, [...]
The Biorobotics Lab reduces complicated high-dimensional problems found in robotics to low-dimensional tractable ones for design, analysis, and planning. Often, we look to biology for inspiration and sometimes, we return the favor by providing analysis that models biology. Our research group runs the full pipeline from basic research, to applied research and all the way to system deployment, and [...]
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 Biomedical Image Guidance (BIG) Lab conducts research in biomedical optics, image analysis, and visualization, especially for intraoperative guidance and also for diagnosis. We use computer vision to assist human placement of biomedical scanners, and we use novel visualization of biomedical images to better guide human manipulation of tools. Applications are wide-ranging, from computer-vision for [...]
Research Topics Computer Vision Light-weighted Deep Learning Visual Perception on Moving Platforms Wearable Human Sensing Applications Computer Vision Surveillance & Security Field Robotics Health Care See more details in my Research Projects Advances in sensors, machine learning and computer vision hold tremendous potential to reshape our world. My research focuses on unlocking this potential contained [...]
Soft Machines Lab The primary focus of my research group is on multifunctional materials for soft robots that are safe for human interaction. In particular, we are developing new materials architectures, solid mechanics models, and fabrication methods that address the following emerging challenges: Elastically soft sensors and circuits for sensorized “artificial skin” and biomechanically compatible stretchable electronics Soft multifunctional [...]
At the Dexterous Manipulation and Soft Robotics lab, we study how hands -- robotic, animated, and human -- grasp, manipulate, and make sense of the physical world. Our research spans the full depth of dexterous manipulation: from the geometry of contact and the biomechanics of the human hand, to algorithms for grasp planning, motion retargeting [...]
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, [...]
My research focuses on computer vision, often motivated by the task of understanding people from visual data. My work tends to make heavy use of machine learning techniques, often using the human visual system as inspiration. For example, temporal processing is a key component of human perception, but is still relatively unexploited in current visual [...]
My specialty is human-robot interaction and advanced transportation. I am interested in how to enable timely and appropriate interaction when interfaces are restricted through design, tasks, the environment, time pressures, and/or user abilities. I utilize training and experience in robotics, intelligent transportation, rehabilitation, human factors and ergonomics, human-computer interaction, universal design, and research methods. My two core areas of [...]
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 [...]
Research interests: computer vision, human activity forecasting, first-person vision, inverse reinforcement learning, deep learning, assistive technologies for people with visual impairment
The control of dynamical systems becomes increasingly important as the era of robotics research dominated by quasi-static machines rapidly comes to a close. Similarly, the importance of state estimation grows as robotic applications require robots to function in larger, more complex environments. My research addresses both of these issues by focusing on the dual problems [...]
My goal has been, and remains, to bring the precision of computer science and applied mathematics to the realities and uncertainties of mechanical systems. I will continue to make fundamental contributions in design, motion planning, path planning, and estimation. Mechanism Design. My group has designed and constructed a variety of snake robots, highly articulated mechanisms [...]
I am interested in advancing the science and technology of legged dynamic systems and in improving through this work the quality of life for people who depend on robotics technology to assist, replace or restore their physical capabilities. We pursue this goal in my group along three interconnected directions: (1) We work on a unified [...]
CV, Research Statement, and Teaching Statement I am a Systems Scientist and Adjunct Assistant Professor at Carnegie Mellon University (CMU), directing the Biomedical Image Guidance Laboratory and teaching an internationally recognized graduate course on medical image analysis algorithms. I have a Ph.D. in Robotics and a B.S. and M.S. in computer engineering. My primary appointment [...]
My research goal is to create systems and methodologies that allow groups of robots and humans to collaborate with one another to perform useful tasks. My research is motivated by an interest in the modeling and control of physical systems on the one hand, and in the creation of effective human-machine interfaces on the other. [...]
Dr. De la Torre's research interests include machine learning, signal processing and computer vision, with a focus on understanding human behavior from multimodal sensors (e.g. video, body sensors). I am particularly interested in three main topics: Component Analysis (CA): CA methods (e.g. kernel PCA, Normalized Cuts, Multidimensional Scaling) are a set of algebraic techniques that decompose [...]
