TensorFleet

Manage, coordinate, and deploy drone & robot fleets.
TensorFleet gives you fleet APIs, mission graphs and ROS/PX4 adapters to go from single drone to production

[TensorFleet @tensorfleetnet]

This could make prototyping missions and autonomy stacks in diverse setups way smoother.

[Nicholas Pfaff @NicholasEPfaff]

Meet SceneSmith: An agentic system that generates entire simulation-ready environments from a single text prompt.

VLM agents collaborate to build scenes with dozens of objects per room, articulated furniture, and full physics properties.

We believe environment generation is no longer the bottleneck for scalable robot training and evaluation in simulation.

Website: https://t.co/UZklSkJe9V

👇🧵(1/8)

[TensorFleet @tensorfleetnet]

@JieWang_ZJUI Interesting read

[TensorFleet @tensorfleetnet]

<1hr fine-tuning for that level of adaptability is a big step forward for real-world deployment testing.

[Skild AI @SkildAI]

Humans learn by watching. Robots should too.

[TensorFleet @tensorfleetnet]

The DeepMind-powered Atlas upgrade and LG’s CLOiD laundry bot show how AI models are finally turning impressive hardware into something practical. Still early, but the gap between demo and deployment feels narrower this year!

[Min Choi @minchoi]

It was only Day 1 of CES 2026.

And the announcements are already mind blowing.

10 wild reveals:

1. Samsung's mysterious slim 3D display

[TensorFleet @tensorfleetnet]

@aakashgupta Totally agree we are on board for this

[TensorFleet @tensorfleetnet]

@boxcardavid We would love to use them

[TensorFleet @tensorfleetnet]

@alpercanbe looks effortless 👏

[TensorFleet @tensorfleetnet]

@physical_int Suddenly youtube level human demos are fair game for robot training

[TensorFleet @tensorfleetnet]

@KuanFang The 3D affordance heatmaps are such a smart way to make robots focus on what they can actually do with objects, instead of getting confused by how things look

[TensorFleet @tensorfleetnet]

@XRoboHub This + open SDKs could flood exhibition spaces with coordinated humanoids faster than we think

[TensorFleet @tensorfleetnet]

@lukas_m_ziegler Great demo! Rectangular (aggressive) for sprint bots.
Trapezoidal for liquids, cameras, and fragile end effectors.

[TensorFleet @tensorfleetnet]

@Keller You guys using magnets ? How are the drones so easily hitting the pads

[TensorFleet @tensorfleetnet]

@UnitreeRobotics Glad to see it. We are adding support for Unitree robots to make the dev much easier

[TensorFleet @tensorfleetnet]

@mfranz_on false positives seem minimal, game changer for prototyping

[TensorFleet @tensorfleetnet]

This release feels like the moment the field levels up.

[Dana Aubakirova @danaaubakir]

Excited to share that LeRobot Community Datasets v3 is here!

50K episodes | 46 robot types | 235 contributors worldwide

One of the largest open-source crowdsourced robot demonstration collections for multi-embodiment learning 🦾

[TensorFleet @tensorfleetnet]

@NVIDIARobotics @RichtechRobots the way it handles those trays so naturally on real hardware shows how good sim-to-real has gotten. Awesome work!

[TensorFleet @tensorfleetnet]

@alexklimaj super awesome !

[TensorFleet @tensorfleetnet]

@alexklimaj super nice!

[TensorFleet @tensorfleetnet]

Depth Anything 3 is going to unlock a lot of interesting use cases for drones. Imagine a security drone mapping out your entire building then easily flying and checking all the floors, no longer need security guards. We can’t wait to integrate these models !

[Bingyi Kang @bingyikang]

After a year of team work, we're thrilled to introduce Depth Anything 3 (DA3)! 🚀

Aiming for human-like spatial perception, DA3 extends monocular depth estimation to any-view scenarios, including single images, multi-view images, and video.

In pursuit of minimal modeling, DA3 reveals two key insights:
💎 A plain transformer (e.g., vanilla DINO) is enough. No specialized architecture.
✨ A single depth-ray representation is enough. No complex 3D tasks.

Three series of models have been released: the main DA3 series, a monocular metric estimation series, and a monocular depth estimation series.

The core team members, aside from me: @HaotongLin, Sili Chen, Jun Hao Liew, @donydchen.

👇(1/n)
#DepthAnything3

[TensorFleet @tensorfleetnet]

@JingxiangMo @gradientrobots Looking forward to play with your sdk and integrate it when it’s ready