Research

The ultimate goal of our research is to develop provably safe autonomous robotic systems that can adapt to 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. Our current research focuses on advanced robotics for manufacturing toward Manufacturing 5.0. Our fundamental research question is: how do we design the behaviors of these robots, and verify the safety of the design, so that they may operate safely, agilely, and interactively in dynamic, uncertain, and human-involved environments.

• Research Overview: Safe, Agile, and Interactive Robotics
• Generative Assembly via Bimanual Manipulation
• Hierarchical Temporal Logic Specifications for Robotic Tasks
• Toward Lifelong Safety of Autonomous Systems in UIE
• Real-Time Systems for Human-Robot Interaction and Industrial Metaverse
• Enhancing and Verifying the Robustness of Learning-based Systems
• Automatic Onsite Grinding of Large Complex Surfaces
• Proactive Safe Human-Robot Interaction
• Safe Uncaged Industrial Robots
• Hierarchical Motion Planning for Efficient and Provably Safe HRI
• 6DoF Robot Assembly Station of Consumer Electronic Production
• Adaptable Behavior Prediction for Autonomous Driving
• Past Projects

back top

Generative Assembly via Bimanual Manipulation

Overview: Assembly is a critical category of tasks in contemporary manufacturing. In particular, we focus on hihg-mix, low-volume (HMLV) assemblies, which are highly customizable, often involving complex operations, such as Lego assembly. Creating an HMLV assembly product is generally time-consuming due to two key factors: 1) designing the assembly and... Read More

Sponsor: CMU Manufacturing Futures Institute
Period of Performance: 2023 ~ Now
Point of Contact: Ruixuan Liu

back top

Hierarchical Temporal Logic Specifications for Robotic Tasks

Overview: Conventional robotic planning, whether task or motion planning, primarily focuses on guiding a robot from an initial state to a target state while avoiding unsafe scenarios. However, with advancements in robotic technology, robots are increasingly expected to perform more complex tasks that go beyond simple point-to-point objectives. For example,... Read More

Period of Performance: 2023 ~ Now
Point of Contact: Xusheng Luo

back top

Toward Lifelong Safety of Autonomous Systems in UIE

Overview The research objective of this proposal is to study the design principles to achieve optimal lifelong safety of autonomous robotic systems in uncertain and interactive environments (UIEs). For example, this capability will enable industrial collaborative robots to safely and optimally work with unfamiliar human workers in novel tasks throughout... Read More

Sponsor: National Science Foundation
Period of Performance: 2022 ~ Now

back top

Real-Time Systems for Human-Robot Interaction and Industrial Metaverse

Overview: Many industrial tasks nowadays require machines to be flexible, i.e., they should be able to 1) understand the changing environments and tasks 2) generate corresponding actions in real time. For example, for machine tending, the manipulators should generate actions regarding the real-time configuration of the materials, which needs to... Read More

Sponsor: Siemens
Period of Performance: 2021 ~ Now
Point of Contact: Yifan Sun

back top

Enhancing and Verifying the Robustness of Learning-based Systems

Overview: Deep Neural Networks (DNNs) play a crucial role in many autonomous systems, particularly in safety-critical applications like autonomous driving. Consequently, it is essential for these learning-based systems to be reliable when making decisions or supporting human decision-making. In this project, we focus on robustness as a key property—ensuring that... Read More

Sponsor: The Boeing Company
Period of Performance: 2023 ~ 2024
Point of Contact: Xusheng Luo, Tianhao Wei

back top

Automatic Onsite Grinding of Large Complex Surfaces

Polishing and grinding of metallic parts is an important manufacturing operation in many industrial applications. It remains challenging to polish large complex surfaces. Polishing is predominantly done manually which is very time consuming, expensive and more importantly, can be a safety hazard for human operators using hand-held devices. We propose... Read More

Sponsor: Advanced Robotics for Manufacturing Institute
Period of Performance: 2019 ~ 2024
Point of Contact: Weiye Zhao

back top

Proactive Safe Human-Robot Interaction

Overview: As robots become more common in industrial manufacturing, social, and home environments, it is imperative that they seamlessly and safely collaborate with humans. This would allow us to take advantage of the speed and precision of robots as well as the flexibility of humans for completing tasks. In this... Read More

Sponsor: CMU Manufacturing Futures Institute
Period of Performance: 2022 ~ 2023
Point of Contact: Ravi Pandya

back top

back top

back top

back top

back top

back top