Stanford MSL
@StanfordMSL
Stanford Multi-robot Systems Laboratory. Endowing groups of robots with the intelligence to collaborate safely and effectively with humans and each other.
Excited to announce Splat-MOVER for multi-stage, open-vocabulary manipulation, with: - Semantic and affordance scene understanding - Scene-editing - Robotic grasp generation! Find out more at splatmover.github.io, and join us Friday, 11/08/24, at the #CoRL2024 poster session.
How much should you trust your robot? Check out our latest paper, where we place sample-efficient confidence bounds on the performance of robots in OOD environments. Project page: tri-ml.github.io/stochastic_ver… ArXiv: arxiv.org/abs/2405.05439
We're excited to present a differentiable physics engine for NeRF-represented objects! We augment object-centric NeRFs with dynamical properties (e.g. friction properties). paper: arxiv.org/abs/2210.09420 video: youtu.be/Md0PM-wv_Xg
Have a deep-learned control system and want to find exact forward and backward reachable sets, control invariant sets, and regions of attraction? Want to know if your neural network has a continuous inverse? All of this and more in our new paper: arxiv.org/abs/2210.08339
Come to our NeRF-Shop today at #ICRA22! We may have some live demos 😊
We're excited to announce our @ieee_ras_icra workshop "Motion Planning with Implicit Neural Representations of Geometry!" We'll discuss the future of INRs -- like DeepSDFs, NeRFs, and more -- in robotics. Submissions due April 15. neural-implicit-workshop.stanford.edu