580 citations · 1.1k across the 18 of their papers we have counts for
18 papers
GrowSplat: Constructing Temporal Digital Twins of Plants with Gaussian Splats
Simeon Adebola, Shuangyu Xie, Chung Min Kim +9
Accurate temporal reconstructions of plant growth are essential for plant phenotyping and breeding, yet remain challenging due to complex geometries, occlusions, and non-rigid defo…
Persistent Object Gaussian Splat (POGS) for Tracking Human and Robot Manipulation of Irregularly Shaped Objects
Justin Yu, Kush Hari, Karim El-Refai +6
Tracking and manipulating irregularly-shaped, previously unseen objects in dynamic environments is important for robotic applications in manufacturing, assembly, and logistics. Rec…
Language-Embedded Gaussian Splats (LEGS): Incrementally Building Room-Scale Representations with a Mobile Robot
Justin Yu, Kush Hari, Kishore Srinivas +9
Building semantic 3D maps is valuable for searching for objects of interest in offices, warehouses, stores, and homes. We present a mapping system that incrementally builds a Langu…
Blox-Net: Generative Design-for-Robot-Assembly Using VLM Supervision, Physics Simulation, and a Robot with Reset
Andrew Goldberg, Kavish Kondap, Tianshuang Qiu +7
Generative AI systems have shown impressive capabilities in creating text, code, and images. Inspired by the rich history of research in industrial ''Design for Assembly'', we intr…
Lifelong LERF: Local 3D Semantic Inventory Monitoring Using FogROS2
Adam Rashid, Chung Min Kim, Justin Kerr +11
Inventory monitoring in homes, factories, and retail stores relies on maintaining data despite objects being swapped, added, removed, or moved. We introduce Lifelong LERF, a method…
GARField: Group Anything with Radiance Fields
Chung Min Kim, Mingxuan Wu, Justin Kerr +3
Grouping is inherently ambiguous due to the multiple levels of granularity in which one can decompose a scene -- should the wheels of an excavator be considered separate or part of…
Language Embedded Radiance Fields for Zero-Shot Task-Oriented Grasping
Adam Rashid, Satvik Sharma, Chung Min Kim +4
Grasping objects by a specific part is often crucial for safety and for executing downstream tasks. Yet, learning-based grasp planners lack this behavior unless they are trained on…
Self-Supervised Learning for Interactive Perception of Surgical Thread for Autonomous Suture Tail-Shortening
Vincent Schorp, Will Panitch, Kaushik Shivakumar +6
Accurate 3D sensing of suturing thread is a challenging problem in automated surgical suturing because of the high state-space complexity, thinness and deformability of the thread,…
LERF: Language Embedded Radiance Fields
Justin Kerr, Chung Min Kim, Ken Goldberg +2
Humans describe the physical world using natural language to refer to specific 3D locations based on a vast range of properties: visual appearance, semantics, abstract associations…
HANDLOOM: Learned Tracing of One-Dimensional Objects for Inspection and Manipulation
Vainavi Viswanath, Kaushik Shivakumar, Jainil Ajmera +6
Tracing - estimating the spatial state of - long deformable linear objects such as cables, threads, hoses, or ropes, is useful for a broad range of tasks in homes, retail, factorie…
Nerfstudio: A Modular Framework for Neural Radiance Field Development
Matthew Tancik, Ethan Weber, Evonne Ng +10
Neural Radiance Fields (NeRF) are a rapidly growing area of research with wide-ranging applications in computer vision, graphics, robotics, and more. In order to streamline the dev…
SGTM 2.0: Autonomously Untangling Long Cables using Interactive Perception
Kaushik Shivakumar, Vainavi Viswanath, Anrui Gu +6
Cables are commonplace in homes, hospitals, and industrial warehouses and are prone to tangling. This paper extends prior work on autonomously untangling long cables by introducing…
Self-Supervised Visuo-Tactile Pretraining to Locate and Follow Garment Features
Justin Kerr, Huang Huang, Albert Wilcox +4
Humans make extensive use of vision and touch as complementary senses, with vision providing global information about the scene and touch measuring local information during manipul…
Autonomously Untangling Long Cables
Vainavi Viswanath, Kaushik Shivakumar, Justin Kerr +7
Cables are ubiquitous in many settings and it is often useful to untangle them. However, cables are prone to self-occlusions and knots, making them difficult to perceive and manipu…
All You Need is LUV: Unsupervised Collection of Labeled Images using Invisible UV Fluorescent Indicators
Brijen Thananjeyan, Justin Kerr, Huang Huang +2
Large-scale semantic image annotation is a significant challenge for learning-based perception systems in robotics. Current approaches often rely on human labelers, which can be ex…
Learning to Localize, Grasp, and Hand Over Unmodified Surgical Needles
Albert Wilcox, Justin Kerr, Brijen Thananjeyan +5
Robotic Surgical Assistants (RSAs) are commonly used to perform minimally invasive surgeries by expert surgeons. However, long procedures filled with tedious and repetitive tasks s…
Dex-NeRF: Using a Neural Radiance Field to Grasp Transparent Objects
Jeffrey Ichnowski, Yahav Avigal, Justin Kerr +1
The ability to grasp and manipulate transparent objects is a major challenge for robots. Existing depth cameras have difficulty detecting, localizing, and inferring the geometry of…
PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learning
Guillaume Sartoretti, Justin Kerr, Yunfei Shi +4
Multi-agent path finding (MAPF) is an essential component of many large-scale, real-world robot deployments, from aerial swarms to warehouse automation. However, despite the commun…