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: Super Odometry helps robots keep their sense of direction when smoke, darkness or dust block their cameras. The system allows robots to rely on internal motion sensors when they can’t see clearly. In real-world tests, it kept robots moving safely through tough conditions like stairs, low light and smoke. *** When a drone [...]
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 [...]
Research includes real-time 3D Lidar SLAM, Lidar Odometry and Mapping (LOAM), navigation, planning, and scene understanding. More on Ji Zhang's page. Multi-robot Collaboration Multiple ground and aerial robots collaboratively explore and map, communicating and leveraging all sensing and mobility modalities across the team to maximize the coverage and efficiency by globally optimizing the plan. Efficient [...]
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 [...]
Our group studies Artificial Intelligence at the intersection of Computer Vision, Machine Learning & Robotics. Our ultimate goal is to build agents with a human-like ability to generalize in real and diverse environments. We believe understanding how to continually develop knowledge and acquire new skills from just raw sensory data will play a vital role [...]
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.
At Generative Intelligence Lab, we are studying the collaboration between Human Creators and Generative Models, with the goal of building intelligent machines capable of helping everyone tell their visual stories. We are studying the following questions: Interaction between creators and generative models: How can we help creators control the model outputs more easily? We develop [...]
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, [...]
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 [...]
LeCar Lab members are broadly interested in the intersection of learning and control, spanning the entire spectrum from theory and foundations, algorithms, to real-world applications in robotics and autonomy. We develop reliable, adaptive, and efficient learning and control methods for embodied intelligence with agility. See our publications and research topics for more details. Videos and [...]
AIIRA’s vision is to create new AI-driven, predictive digital twins for modeling plants, and deploy them to increase the resiliency of the nation’s agricultural systems. AIIRA's institutions cover three of the five major areas of the US mainland, including Midwest, Southwest, and Northeast with stakeholders composed of companies, governmental agencies, commodity groups, prominent centers, and [...]
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.
The Safe AI Lab at CMU aims to develop reliable, explainable, verifiable, and good-for-all artificial intelligent learning methods for consequential applications in the face of the uncertain, dynamic, time-varying, multiple agents, and possibly human-involved environment by bridging fundamental learning theories and engineering technologies.
My research interests are in the intersection of machine learning and control theory, spanning the entire spectrum from theory and foundations, and practical algorithms, to real-world applications in robotics and autonomy. To that end, there are three goals: (1) bridge learning and control theory in a unified framework; (2) design reliable learning and control algorithms [...]
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.
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, [...]
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.
The Carnegie Mellon University Navigation Laboratory group builds computer-controlled vehicles for automated and assisted driving. Since 1984, we have built a series of robot cars, vans, SUVs, and buses. More recent research expands to smart infrastructure, focusing on machine vision application and affordable sensors. The CMU Center for Autonomous Vehicle Research website is an up-to-date [...]
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 [...]
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 [...]
At the Generative Intelligence Lab, we are studying the collaboration between Human Creators and Generative Models, with the goal of building intelligent machines capable of helping everyone tell their visual stories. We are studying the following questions: Interaction between creators and generative models: How can we help creators control the model outputs more easily? We [...]
My ultimate goal is to build agents with a human-like ability to generalize in real and diverse environments. I believe understanding how to continually develop knowledge and acquire new skills from just raw sensory data will play a vital role in achieving this goal. I draw inspiration from psychology to build practical systems at the [...]
There is an increasing demand for more adaptable, mobile, and flexible robots in complex environments. In Zoom Lab, solutions focus on learning and controls algorithms and embedded intelligence in mechanical structures. We explore designing novel robotic systems inspired by biology: Zoom in to understand the mechanisms of small scale physics of locomotion in different environments [...]
The Resilient Intelligent Systems Lab (RISLab) is part of Carnegie Mellon University’s Robotics Institute. The lab, led by Director Wennie Tabib, is focused on resilient autonomy and agile flight in complex, unstructured environments. https://www.rislab.org
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 [...]
Research: Leading the CMU Safe AI Laboratory, Zhao aims to create trustworthy AI that is robust, safe, generalizable as well as explainable, verifiable, and human-centric. His long-term goal is to develop fundamental theories and practical technologies to safely deploy AI to address some of the world's most pressing problems. Zhao is recognized nationally and internationally [...]
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 [...]
I am an Assistant Professor in the Robotics Institute at Carnegie Mellon University, where I lead the Zoom Lab. I’m interested in bio-inspired solutions to increase mechanical intelligence in robots and robotic components. Current robots are primarily rigid machines that exist in highly constrained or open environments such as factory floors, warehouses, or fields. There [...]
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 focuses on developing algorithms and representations to enable robots to learn versatile manipulation skills over time. The ability to learn skills and adapt manipulations to new situations will open up a wide range of new robot applications, including taking care of the elderly, maintaining parks and public places, and assisting in hazardous environments. [...]
My research lies at the intersection of robotics, machine learning, and computer vision. I am interested in developing methods for robotic perception and control that can allow robots to operate in the messy, cluttered environments of our daily lives. My approach is to design new deep learning / machine learning algorithms to understand environmental changes: [...]
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 [...]
Search-based Planning Laboratory researches methodologies and algorithms that enable autonomous systems to act fast, intelligently and robustly. Our research concentrates mostly on developing novel planning approaches, coming up with novel heuristic searches and investigating how planning can be combined with machine learning. Our work spans graph theory, algorithms, data structures, machine learning and of course [...]
The Auton Lab, part of Carnegie Mellon University's School of Computer Science, researches new approaches to Statistical Data Mining. It is directed by Artur Dubrawski, Andrew Moore and Jeff Schneider. We are very interested in the underlying computer science, mathematics, statistics and AI of detection and exploitation of patterns in data. We build practical large-scale [...]
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 [...]
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 [...]
Please visit the official Computer Graphics Lab website for current information - thank you!
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 [...]
Problems of large-scale coordination and logistics are ubiquitous, and better solutions are becoming increasingly critical in many domains. In manufacturing, trends toward industrial globalization and constrained market focus on high value-adding products, together with new coordination concepts such as electronic marketplaces, require organizations to become more agile. Military command and control infra-structure is faced with [...]
My research interests are in the area of intelligent vehicles and autonomous driving in urban areas with an emphasis on development of a short range laser triangulation sensor and its application, and the short term prediction and analysis of future vehicle and object movements.
My research interests are in Computer Vision, Digital Humans, and Computational Behavior Science, specifically in areas of modeling, understanding, and synthesizing human motion and behavior using diverse sensors. Currently I am directing the CUBE Lab. The research in the Computational Behavior (CUBE) Lab broadly focuses on computer vision and machine learning for behavior science and [...]
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 [...]
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 research is in active learning, data mining, reinforcement learning, optimization, and intelligent control. My efforts are focused on the application of these methods to real world industrial and commercial problems.
My research interests are in artificial intelligence, primarily in the areas of constraint-based search and optimization, automated planning and scheduling, configurable and adaptive problem solving systems, multi-agent and multi-robot coordination, mixed-initiative decision-making, and naturally inspired search procedures. One integrating focus has been the development of core technologies for coordination and control of large-scale, multi-actor systems, [...]
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 [...]
My general research interests lie in Artificial Intelligence and Robotics. More specifically, they currently cover planning in deterministic and probabilistic domains and machine learning. My research has been mainly motivated by the problem of fast and intelligent decision making by autonomous robotic systems operating in real-world environments. Some of the robotic systems my group does [...]
My research focuses on the coordination and control of dynamic physical systems, both natural and human-made and explores techniques that may someday allow robots and animated creatures to plan and control their actions in complex and unpredictable environments while interacting with humans. To make progress toward this goal, I have active projects in computer graphics, [...]
Efficient techniques for object/category recognition Use of contextual information, in particular 3-D geometry from images, for scene analysis Symbolic knowledge for scene interpretation and reconstruction Motion analysis for feature extraction and event detection in video clips Efficient tools for the analysis of dynamic 3-D point clouds ("3-D signal processing") Perception for autonomous systems Detection, tracking, [...]
I am interested in intelligent systems that work, are useful, and make economic sense, and in finding ways to effectively build and deploy them. My work is driven by real-world applications, currently in the areas of public health, food safety, nuclear safety and health of equipment. It involves researching new machine learning algorithms and data [...]
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. [...]
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 [...]
