activity
20242026
collaborators

9 papers

cs.CV2026

Hydra++: Real-Time Hierarchical 3D Scene Graph Construction With Object-Level Shape Estimation

Hyungtae Lim, Nathan Hughes, Xihang Yu +5

3D scene graphs provide a hierarchical abstraction of environments by encoding spatial entities, such as objects and places, and their relationships. However, existing scene graph…

cs.RO2026

Hierarchical Object Representation for Spatial Robot Perception: Points, Meshes, and Superquadrics

Ceng Zhang, Wan Su, Mohamed Samshad +2

Hierarchical 3D Scene Graphs (3DSG) have emerged as an actionable and scalable representation for long-term autonomy incorporating metric, semantic, and topological information in…

cs.CV2026

Picasso: Holistic Scene Reconstruction with Physics-Constrained Sampling

Xihang Yu, Rajat Talak, Lorenzo Shaikewitz +1

In the presence of occlusions and measurement noise, geometrically accurate scene reconstructions -- which fit the sensor data -- can still be physically incorrect. For instance, w…

cs.RO2026

Object Pose and Shape Estimation for Grasping: Does it Work?

Pavan Karke, Kushal Shah, Gaurav Singh +3

The problem of object pose and shape estimation has seen key advancements lately. Encoder-decoder (e.g., SAM3D, LRM, CRISP) and diffusion-based models (e.g., InstantMesh, Zero123,…

cs.RO2025

Language-Grounded Hierarchical Planning and Execution with Multi-Robot 3D Scene Graphs

Jared Strader, Aaron Ray, Jacob Arkin +11

In this paper, we introduce a multi-robot system that integrates mapping, localization, and task and motion planning (TAMP) enabled by 3D scene graphs to execute complex instructio…

cs.RO2025

Box Pose and Shape Estimation and Domain Adaptation for Large-Scale Warehouse Automation

Xihang Yu, Rajat Talak, Jingnan Shi +3

Modern warehouse automation systems rely on fleets of intelligent robots that generate vast amounts of data -- most of which remains unannotated. This paper develops a self-supervi…