DRONEFORGE

Building the intelligence layer for everyday drones. Nimbus adds object tracking, repeatable routes, and programmable autonomy. Starting at $159!

[DRONEFORGE @droneforge]

Official paper: https://t.co/2t6W7qTtK2
Official GitHub: https://t.co/L7Zi5gMWag

[DRONEFORGE @droneforge]

🚨 New Drone Simulator

[5.31.2026] Researchers release CrazyFlow - a GPU accelerated, differentiable simulator in JAX.

Benchmarked on a RTX4090:
> Parallel sim: ~700M steps/s at 1M worlds
> Max scale: 4.2M drones, 900M+ steps/s
> Gradients: 9M gradients/s through 10 sim steps
> Depth rendering: 350k frames/s at 64x64 over 1,024 envs

Read our 11 minute research note on the paper: https://t.co/OYXmRNQ6pt

[DRONEFORGE @droneforge]

FLIP is a new swarm-planning method that keeps 100 drones coordinating in real time by treating formation changes like point-cloud registration

In the paper’s benchmark, FLIP planned for 100 drones in ~0.040s mean time, compared with ~0.933s for Zhou’s method and ~5.814s for Quan’s

The useful part is that it's fast enough for large swarms and resilient to single-agent failures or mid flights adaptations

Read our 12 minute notes: https://t.co/R5ySPsPGha

Or the original paper by Zhou, Xu, Hou, Hou, Gao, at:
https://t.co/Un1NY4ZKkH

[DRONEFORGE @droneforge]

New community hub just dropped for drone x ai enthusiasts

We'll be posting weekly:
> Changelogs
> SOTA research of the week
> Open sourced GitHub repos examples

Check it out:
https://t.co/NryQt53Mgq

[DRONEFORGE @droneforge]

How to troubleshoot state estimation issues?

All you need is April tags and some computer vision

[Chester @chesterzelaya]

Snow White had birds

Droneforge has autonomous drones

[DRONEFORGE @droneforge]

@StrykerFromFL Good idea — will make it a website feature by next week

[DRONEFORGE @droneforge]

Welcome to Droneforge Email Newsletter

We’re going to start covering:
> weekly app changelogs
> top drone research of the week
> tutorials and guides for Nimbus

Want to stay updated? DM us your email and we’ll add you to the list

[DRONEFORGE @droneforge]

DRONEFORGE 2.1.4 RELEASE

In our most anticipated update -- we expose a full python interface to program your FPV drones using our DF1 autonomy stack

Use our out-of-the-box autonomy stack to create your own AI drone missions

Check out our docs!
https://t.co/uNExT6PAql

[DRONEFORGE @droneforge]

@rahim_mirani @southpkcommons @HrishikeshMB

[DRONEFORGE @droneforge]

@MountsOwen holy W

[DRONEFORGE @droneforge]

interested in deploying RL policies on drones? we are the quickest path to deployment!

https://t.co/1wqAxBvT6j

[DRONEFORGE @droneforge]

🚨 Adversarial RL for Drone Interceptors:

Competitive RL is being used to train drone interceptors against agile evasive drones

But instead of training only the interceptor (pursuer), this paper trains both sides.

1. The interceptor learns to catch
2. The evader learns to escape

Making autonomy adversarial pushes both policies to its limits. Both agents are trained inside a high-fidelity JAX quadrotor simulator running massive parallel rollouts

Results showed a successful transfer zero-shot to a real indoor flight arena, and caught the simulated evader 7 times in 28 seconds.

Paper: https://t.co/FZw2W7g6Uy

[DRONEFORGE @droneforge]

@aussetg no ITAR stuff, but the frequencies on our TX module could land you in trouble with the communications department of your country

[DRONEFORGE @droneforge]

Droneforge is an ode to the goodness of robotics

To the celebration of accessibility and the powerful intelligence that will change the world for the better

[DRONEFORGE @droneforge]

Building toward more useful, programmable drones at Droneforge -- check us out!

https://t.co/1wqAxBvT6j

[DRONEFORGE @droneforge]

🚨Awesome UAV Datasets
(specifically curated for training VLA's)

> Synthetic UAV Flight Trajectories — Hugging Face dataset with 5,000+ synthetic UAV trajectories over ~20 hours of flight time
https://t.co/EEPjciW8O2

> U2UData+ / U2UData-2 — Large-scale swarm UAV autonomous flight dataset: 15 UAVs, 12 scenes, 720 traces, 120 hours, 600 seconds per trajectory, with RGB, depth/LiDAR, and environmental signals
https://t.co/mtgAiSq88l

> CognitiveDrone Dataset — 8,062 simulated UAV flight trajectories for VLA-style drone control, split across human recognition, symbol understanding, and reasoning tasks
https://t.co/rzint94UhL

> AutoFly Dataset — VLA-style UAV autonomous navigation dataset with 13K+ episodes and 2.5M image-language-action triplets, built from expert demonstrations and simulated trajectories, plus 1K real-world flight episodes for sim-to-real validation
https://t.co/tNkh44ivC0

> UAV-Flow / UAV-Flow-Sim — Real-world language-conditioned UAV imitation-learning benchmark with 30,692 real UAV flight trajectories and 10,109 simulated trajectories, where each sample includes language instruction, egocentric visual observation, and 6-DoF UAV state/action trajectories
https://t.co/yRGwTT1eFE

[DRONEFORGE @droneforge]

@aussetg shoot :(
we aren’t certified to ship outside US

[DRONEFORGE @droneforge]

@aussetg you can soon :)!

we are open sourcing our python library next week to create your own state estimation pipelines! would love to see what you can cook up