Building Robot Hands and Teaching Dexterity
Abstract: Our human hands are masterpieces of power and precision, capable of typing, hammering, or delicately using chopsticks. Yet most robots today still rely on simple two-finger grippers in controlled settings because dexterous hands are costly and difficult to deploy. To close this gap, I will introduce my LEAP Hands, high-performance, low-cost, and easy-to-assemble robotic [...]
Grounded Task Axes: Zero-Shot Semantic Skill Generalization via Task-Axis Controllers and Visual Foundation Models
Abstract: Transferring skills between different objects remains one of the core challenges of open-world robot manipulation. Generalization needs to take into account the high-level structural differences between distinct objects while still maintaining similar low-level interaction control. In this paper, we propose an example-based zero-shot approach to skill transfer. Rather than treating skills as atomic, we [...]
OpenVDB
Abstract: As the inventor of VDB and founder of OpenVDB, I am excited to talk about its history, motivation, and diverse adoption. Specifically, this lecture will cover the underlying VDB data structure, and its adoption to computer graphics, physics simulations and more recently machine learning. Since its open-source release in 2012, OpenVDB has become an industry [...]
How to Coordinate Thousands of Robots Efficiently and Robustly
Abstract: Large-scale robot fleets are increasingly deployed in warehouses, factories, transportation systems, and emerging robotics applications. Coordinating hundreds or thousands of robots in shared, cluttered spaces creates fundamental challenges in maintaining safety, preventing deadlocks, and minimizing congestion. In this talk, I will present our recent work on scalable imitation learning methods for coordinating 10k robots, automatic environment [...]
Sensorimotor-Aligned Design for Pareto-Efficient Haptic Immersion in Extended Reality
Abstract: A new category of computing devices has emerged: augmented and virtual reality headsets, collectively referred to as extended reality (XR). These devices can alter, augment, or even replace our reality. While these headsets have made impressive strides in audio-visual immersion over the past half-century, XR interactions remain almost completely absent of appropriately expressive tactile [...]
Multi-View 4D Human Reconstruction under Interaction Scenarios
Abstract: Building large-scale human datasets from multi-view videos is essential for advancing research in human behavior understanding, virtual reality, animation, and robotics. Compared to traditional motion capture systems that rely on physical markers to track motion, vision-based reconstruction not only enables the capture of human motion in unconstrained environments but also avoids altering human appearance [...]
Vision-Based Multi-Wire Detection and Tracking for UAV Wire Approach
Abstract: Reliable detection and tracking of power lines is critical for enabling under-wire UAV approach and inductive power-line charging to extend UAV range. However, wires are thin, featureless, and visually ambiguous structures that challenge traditional computer vision methods and degrade depth estimation accuracy. To address these challenges, this thesis presents a fully passive, camera-only multi-wire [...]
Towards Scaling Embodied Data for Robot Learning
Abstract: As artificial intelligence advances quickly in the digital domain, the next frontier lies in physical intelligence: systems that learn through acting and sensing in the real world. In this thesis, we explore practical ways of scaling such embodied data across three directions. AnyCar scales synthetic data through large-scale simulation, training a universal dynamics transformer [...]
Attractors and Their Applications in Heuristic Search
Abstract: Heuristic search provides a principled way to guide exploration in large state spaces, enabling efficient solution finding. As a result, it is widely used across domains such as robotics, games, and planning. However, its performance is often limited by memory consumption and computational overhead, which have motivated extensive research on improving both. This thesis [...]
Robotic System Design Principles for Human-Human Collaboration
Abstract: Robots possess unique affordances granted by combining software and hardware. Most existing research focuses on the impact of these affordances on human-robot collaboration, but the theory of how robots can facilitate human-human collaboration is underdeveloped. Such a theory would be beneficial in education. An educational device can afford collaboration in both assembly and use. [...]