PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Continual Learning of Compositional Skills for Robust Robot Manipulation

GHC 6501

Abstract: Real world robots need to continuously learn new manipulation tasks in a lifelong learning manner. These new tasks often share many sub-structures e.g. sub-tasks, controllers, preconditions, with previously learned tasks. To utilize these shared sub-structures, we explore a compositional and object-centric approach to learn manipulation tasks. The first part of this thesis focuses on [...]

VASC Seminar
Zhenglun Kong
Ph.D. in the Department of Electrical and Computer Engineering
Northeastern University

Towards Energy-Efficient Techniques and Applications for Universal AI Implementation

Newell-Simon Hall 3305

Abstract: The rapid advancement of large-scale language and vision models has significantly propelled the AI domain. We now see AI enriching everyday life in numerous ways – from community and shared virtual reality experiences to autonomous vehicles, healthcare innovations, and accessibility technologies, among others. Central to these developments is the real-time implementation of high-quality deep [...]

Faculty Events

RI Faculty Business Meeting

Newell-Simon Hall 4305

Meeting for RI Faculty. Discussions include various department topics, policies, and procedures. Generally meets weekly.

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Watch, Practice, Improve: Towards In-the-wild Manipulation

GHC 4405

Abstract: The longstanding dream of many roboticists is to see robots perform diverse tasks in diverse environments. To build such a robot that can operate anywhere, many methods train on robotic interaction data. While these approaches have led to significant advances, they rely on heavily engineered setups or high amounts of supervision, neither of which [...]

VASC Seminar
Shengjie Zhu
Ph.D. Student
Michigan State University

Structure-from-Motion Meets Self-supervised Learning

Newell-Simon Hall 3305

Abstract: How to teach machine to perceive 3D world from unlabeled videos? We will present new solution via incorporating Structure-from-Motion (SfM) into self-supervised model learning. Given RGB inputs, deep models learn to regress depth and correspondence. With the two inputs, we introduce a camera localization algorithm that searches for certified global optimal poses. However, the [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Combining Physics-Based Light Transport and Neural Fields for Robust Inverse Rendering

NSH 3305

Abstract:   Inverse rendering — the process of recovering shape, material, and/or lighting of an object or environment from a set of images — is essential for applications in robotics and elsewhere, from AR/VR to perception on self-driving vehicles. While it is possible to perform inverse rendering from color images alone, it is often far easier [...]

PhD Thesis Defense
Extern
Robotics Institute,
Carnegie Mellon University

Improving the Transparency of Agent Decision Making to Humans Using Demonstrations

GHC 4405

Abstract: For intelligent agents (e.g. robots) to be seamlessly integrated into human society, humans must be able to understand their decision making. For example, the decision making of autonomous cars must be clear to the engineers certifying their safety, passengers riding them, and nearby drivers negotiating the road simultaneously. As an agent's decision making depends [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Robotic Climbing for Extreme Terrain Exploration

NSH 3305

Abstract: Climbing robots can operate in steep and unstructured environments that are inaccessible to other ground robots, with applications ranging from the inspection of artificial structures on Earth to the exploration of natural terrain features throughout the solar system. Climbing robots for planetary exploration face many challenges to deployment, including mass restrictions, irregular surface features, [...]

RI Event
Assistant Professor
Robotics Institute,
Carnegie Mellon University

Layout Design for Large-Scale Multi-Robot Coordination

Newell-Simon Hall 4305

Abstract: Today, thousands of robots are navigating autonomously in warehouses, transporting goods from one location to another. While numerous planning algorithms are developed to coordinate robots more efficiently and robustly, warehouse layouts remain largely unchanged – they still adhere to the traditional pattern designed for human workers rather than robots. In this talk, I will [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Perception amidst interaction: spatial AI with vision and touch for robot manipulation

GHC 6501

Abstract: Robots currently lack the cognition to replicate even a fraction of the tasks humans do, a trend summarized by Moravec's Paradox. Humans effortlessly combine their senses for everyday interactions—we can rummage through our pockets in search of our keys, and deftly insert them to unlock our front door. Before robots can demonstrate such dexterity, [...]