Search Results for author:
Found 7 papers, 2 papers with code
Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy
In this paper, we propose a novel SSM-based point cloud processing backbone, named Point Mamba, with a causality-aware ordering mechanism.
MultiPLY: A Multisensory Object-Centric Embodied Large Language Model in 3D World
Human beings possess the capability to multiply a melange of multisensory cues while actively exploring and interacting with the 3D world.
RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation
We present RoboGen, a generative robotic agent that automatically learns diverse robotic skills at scale via generative simulation.
Mixup-Augmented Meta-Learning for Sample-Efficient Fine-Tuning of Protein Simulators
Molecular dynamics simulations have emerged as a fundamental instrument for studying biomolecules.
Towards Generalist Robots: A Promising Paradigm via Generative Simulation
This document serves as a position paper that outlines the authors' vision for a potential pathway towards generalist robots.
AdaAfford: Learning to Adapt Manipulation Affordance for 3D Articulated Objects via Few-shot Interactions
Perceiving and interacting with 3D articulated objects, such as cabinets, doors, and faucets, pose particular challenges for future home-assistant robots performing daily tasks in human environments.
VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objects
In this paper, we propose object-centric actionable visual priors as a novel perception-interaction handshaking point that the perception system outputs more actionable guidance than kinematic structure estimation, by predicting dense geometry-aware, interaction-aware, and task-aware visual action affordance and trajectory proposals.
