Put Quaddle on a patch of gravel and just wanted to see it walk. Its IMU (gyroscope + accelerometer) was trying to correct for the uneven ground in real time, but it just started wobbling — loose gravel is apparently brutal for a quadruped's balance.

What other terrains should Quaddle try?

It's a pair of animatronic eyes: two servos (left/right and up/down), a frame I designed and 3D printed, and an Arduino UNO.

The hardest part wasn't the mechanism, it was making it easy to program. I wanted someone who has never coded to get it moving without fighting with IDE installs, drivers and libraries. So I made a web app:

- Block-based programming (Scratch-style) in Spanish: "look left", "wait 1 second", "nod yes"...

- A simulator that shows how the eyes will move before you plug anything in.

- Plug the Arduino in over USB and upload straight from the browser (Chrome or Edge).

- Every block shows its C++ line, so you can see the real code or download it as an .ino.

Video of it working below.

I'd like to turn it into an educational kit eventually, but I'm still refining a lot, so I'd love your feedback:

1. What would you improve in the mechanism or design?

2. If you were teaching someone with this, what blocks or features would you add?

3. Anyone used Web Serial for something like this? Any pitfalls I should know about?

Happy to chat by DM if anyone wants to know more or has ideas.

Hice unos ojos animatrónicos y una app web para programarlos con bloques, sin instalar nada

Hola! Soy estudiante de Ingeniería en Control Automático y Robótica y llevo un tiempo trabajando en este proyecto personal.

Son unos ojos animatrónicos con dos servos (uno para los lados y otro para arriba/abajo), una estructura que diseñé e imprimí en 3D, y un Arduino UNO.

Lo que más me costó no fue el mecanismo, sino la parte de programarlo. Quería que alguien que nunca ha programado pudiera hacerlo moverse sin pelearse con instalar el IDE, drivers y librerías. Así que hice una app web:

- Programas con bloques en español (tipo Scratch): "mirar a la izquierda", "esperar 1 segundo", "decir que sí"...

- Tiene un simulador para ver cómo se moverían los ojos antes de conectar nada.

- Conectas el Arduino por USB y lo subes desde el navegador (Chrome o Edge).

- Cada bloque muestra su línea en C++, por si quieres ver el código real o descargarlo como .ino.

Les dejo un video de cómo funciona.

Mi idea es convertirlo en un kit educativo para que más gente aprenda así, pero todavía estoy afinando muchas cosas, por eso me encantaría su opinión:

1. ¿Qué le mejorarían al mecanismo o al diseño?

2. Si fueran a enseñarle a alguien con esto, ¿qué bloques o funciones le agregarían?

3. ¿Les ha tocado usar Web Serial en proyectos así? ¿Algún problema que deba tomar en cuenta?

Si alguien quiere saber más del proyecto, busca apoyarlo o tiene ideas, con gusto platico por mensaje privado.

This is TAKTO ONE, a tendon-driven hand exoskeleton I built for my master’s thesis. Each of the 12 finger joints has its own magnetic encoder, and the twin in the headset moves from those sensors and two IMUs, not from camera tracking, so a hidden finger still gets measured.

It’s all open source (CAD, PCBs, firmware, build guide), and you can play with the twin in your browser, no hardware needed:
https://takto.one
https://github.com/molanocortes/takto-one

I defend the thesis tomorrow, so questions are very welcome :)

I own an online store. Daily I get emails where a customer explains, with complete certainty, how my own product works, what my terms say, or what the law requires. Beautifully written, full of jargon, and often completely wrong.

I use AI every day myself, so this isn't an anti-AI post. But people stopped separating "AI told me" from "this is true".

Is this just a phase until people learn how to use it, or are we watching people outsource thinking at scale?

Small experiment from this week. I connected LightNav-0 (an open vision-language navigation model) to the Microduck sim in MuJoCo.

The duck takes an instruction like "go to the wooden doorframe and stop", predicts a path from its first-person frames, and the motion is executed via MPC + its official ONNX gait policy.

Everything runs on-device on a Jetson AGX Orin 32GB power by reComputer Robotics J501 form seeed, no cloud. The loop: 4 Hz frames → path prediction on the GPU → MPC → gait policy on CPU. 200 Hz physics, real-time factor ≈ 1.

It's a sim dev preview and I'm not claiming task success yet; strict benchmarks are still in progress. This is heading into Module 7 (Vision-Language Navigation) of our open mobile robot course: mobile-robot-full-stack-course

Happy to answer questions about the setup. 🦆

Source https://youtu.be/lkjbQe-hqrw

Look at my robot spider. I can programme and let him to do whatever I want. Kick the ball, push the obstacles, wave to me . I can explore more.

For more about it. https://x.com/_doubleAI_/status/2107554526563606600

Ben Affleck sat down for a surprisingly technical interview discussing tensors, convolutional neural networks, and why video generation scaling is entirely different from LLMs.

I feel like more people blame ai for ai slop than the people who tell ai to generate ai slop.