We build spatial intelligence for robots. Right now that means a SLAM based drone, built and tested in simulation first, so it can map, plan and fly where GPS cannot reach.
Tactile sensing for robots explained: the four sensor types, why raw touch data fails, and how LingBot-Touch lifts success to 70%, with Python code.
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Robotics Agentic Robotics Explained 10 Nov 2026 · 13 min read 
Robotics VLA Inference Latency Explained 4 Nov 2026 · 13 min read 
Robotics Robot Gyms vs Simulation 1 Nov 2026 · 12 min read 
Robotics How Drones Fly Without GPS 30 Oct 2026 · 15 min read 
Robotics World Models for Robots Explained 29 Oct 2026 · 11 min read Four areas, one goal: a robot that knows where it is and decides well what to do next.
Visual and inertial mapping that keeps a robot localized indoors, underground and anywhere satellites drop out, with planners that turn the map into a safe route.
Perception that runs on the robot itself: detection and recognition today, and learned 3D models that make maps denser and tracking more reliable.
Robots that learn decisions from experience, built on the math of Markov decision processes.
Robots that learn skills by watching people, and the hardware and control that let them act on what they learn.
Veg maps its surroundings with visual inertial SLAM, plans its own route, recognises people and objects onboard and lands safely after a rotor failure. The research version runs entirely on a Raspberry Pi 4 and an Arduino Nano, and is described in a paper on arXiv.
Now: building Veg 3.0 in simulation
New to a topic? Each path goes from the basics to this year's research, one article at a time.
We are looking for research partners, pilot customers and engineers who want robots that work without GPS.
