Recent advances in 3d gaussian splatting

T Wu, YJ Yuan, LX Zhang, J Yang, YP Cao… - Computational Visual …, 2024 - Springer
The emergence of 3D Gaussian splatting (3DGS) has greatly accelerated rendering in novel
view synthesis. Unlike neural implicit representations like neural radiance fields (NeRFs) …

Dreamphysics: Learning physical properties of dynamic 3d gaussians with video diffusion priors

T Huang, H Zhang, Y Zeng, Z Zhang, H Li… - arXiv preprint arXiv …, 2024 - arxiv.org
Dynamic 3D interaction has been attracting a lot of attention recently. However, creating
such 4D content remains challenging. One solution is to animate 3D scenes with physics …

Graspsplats: Efficient manipulation with 3d feature splatting

M Ji, RZ Qiu, X Zou, X Wang - arXiv preprint arXiv:2409.02084, 2024 - arxiv.org
The ability for robots to perform efficient and zero-shot grasping of object parts is crucial for
practical applications and is becoming prevalent with recent advances in Vision-Language …

Robo-gs: A physics consistent spatial-temporal model for robotic arm with hybrid representation

H Lou, Y Liu, Y Pan, Y Geng, J Chen, W Ma… - arXiv preprint arXiv …, 2024 - arxiv.org
Real2Sim2Real plays a critical role in robotic arm control and reinforcement learning, yet
bridging this gap remains a significant challenge due to the complex physical properties of …

SAD-GS: Shape-aligned Depth-supervised Gaussian Splatting

PC Kung, S Isaacson, R Vasudevan… - Proceedings of the …, 2024 - openaccess.thecvf.com
This paper proposes SAD-GS a depth-supervised Gaussian Splatting (GS) method that
provides accurate 3D geometry reconstruction by introducing a shape-aligned depth …

A survey of embodied learning for object-centric robotic manipulation

Y Zheng, L Yao, Y Su, Y Zhang, Y Wang… - arXiv preprint arXiv …, 2024 - arxiv.org
Embodied learning for object-centric robotic manipulation is a rapidly developing and
challenging area in embodied AI. It is crucial for advancing next-generation intelligent robots …

Neural Fields in Robotics: A Survey

MZ Irshad, M Comi, YC Lin, N Heppert… - arXiv preprint arXiv …, 2024 - arxiv.org
Neural Fields have emerged as a transformative approach for 3D scene representation in
computer vision and robotics, enabling accurate inference of geometry, 3D semantics, and …

Open-vocabulary mobile manipulation in unseen dynamic environments with 3d semantic maps

D Qiu, W Ma, Z Pan, H Xiong, J Liang - arXiv preprint arXiv:2406.18115, 2024 - arxiv.org
Open-Vocabulary Mobile Manipulation (OVMM) is a crucial capability for autonomous
robots, especially when faced with the challenges posed by unknown and dynamic …

Next Best Sense: Guiding Vision and Touch with FisherRF for 3D Gaussian Splatting

M Strong, B Lei, A Swann, W Jiang, K Daniilidis… - arXiv preprint arXiv …, 2024 - arxiv.org
We propose a framework for active next best view and touch selection for robotic
manipulators using 3D Gaussian Splatting (3DGS). 3DGS is emerging as a useful explicit …

RL-GSBridge: 3D Gaussian Splatting Based Real2Sim2Real Method for Robotic Manipulation Learning

Y Wu, L Pan, W Wu, G Wang, Y Miao… - arXiv preprint arXiv …, 2024 - arxiv.org
Sim-to-Real refers to the process of transferring policies learned in simulation to the real
world, which is crucial for achieving practical robotics applications. However, recent …