Hello, I have recently graduated from computer science and I want to join robotics engineering. I only have software and AI related knowledge but no electrical, circuit, and mechanical knowledge. Can I survive in this field, and also, can I get a job as fresher? I have no prior experience.

What new things I have to study to get into this field?

ok so this has been living in my head for like a week now. apparently there are thousands of people in india just wearing cameras on their heads while making chai or folding clothes or doing factory work, and that footage gets sold to robotics labs to train robots?? which is kind of wild when you think about it. but then i kept wondering, does a robot even learn anything from watching a human hand, it doesn't have fingers lol it has like two metal jaws. then i found this paper from UMD called HumanEgo and they trained robots with only human video, zero robot demos, around 30 mins per task, and got 92.5% success, while teleop with the same time got 51.2%, which kinda blew my mind.

but then you read how they did it and it's fancy aria glasses with SLAM and calibrated hand tracking and they literally paint out the human arm and draw a gripper there instead, so it's not exactly some guy with a gopro on his forehead..... and they still say it's not super precise. so now i'm thinking half the footage being collected is probably not worth much?

i read somewhere clients reject videos because the table colour was wrong or the lighting was off which is honestly funny. anyway has anyone here actually tried mixing human video with teleop data, does it actually help or does it stop mattering after some point, and what happens with harder hand stuff. idk just curious.

🤖 Robot Forearm | 3-DOF Robotic Wrist & Articulated Hand・Fichier 3D pour Impression 3D・Cults

🤖 Robot Forearm | 3-DOF Robotic Wrist & Articulated Hand・Fichier 3D pour Impression 3D・Cults

Hey everyone!

I've recently turned Assetto Corsa into an autonomous driving simulator. The reason I started this project is that I realized there aren't really many good options out there for people who want to get into autonomous racing.

Real race cars are incredibly expensive. Even an F1TENTH car costs several thousand dollars, and still need a dedicated space to drive it. On the other hand, existing open-source simulators often leave a lot to be desired in terms of physics and graphics.

So I decided to integrate cameras and LiDAR sensors into Assetto Corsa and connect everything to ROS.

Here's what I've implemented so far:

- Camera ground truth: any number of virtual cameras; RGB, depth and semantic segmentation in sync every frame; 2D boxes aligned to the pixel

- LiDAR simulation: spinning LiDARs with custom scan patterns, solid-state LiDARs with real measured patterns; 3D boxes frame-aligned with the point cloud

- Semantic annotation and map editing: click-to-assign over the whole track, reusing the entire AC mod ecosystem;

- Telemetry

- ROS 2 support https://github.com/Utschie/ac_ros2_bridge and https://github.com/Utschie/ac_msgs

- Dataset generation

It's already usable, and the fps is pretty decent (more than enough for autonomous driving cameras).

The project is still under development, so I haven't set up a website for it yet. Here's what I'm planning to work on next:

• Improve the LiDAR point clouds,

• Add more sensors, including radar, IMU, and GPS

• Make the physics simulation speed adjustable

If anyone is interested in trying it out, feel free to reach out! I'd be happy to share the installer with you.

🤖 Turning code into motion, one line at a time! ⚡🏎️

Building and testing my 16-sensor Line Following Robot using Arduino Nano, IR sensors, N20 motors, and PID-based control.

Every turn is a challenge. Every test is a lesson. Every iteration brings me closer to building faster and smarter robots. 🚀

Next goal: Custom PCB, optimized chassis, and high-speed performance! 🔧

This is just the beginning. 💻⚙️

#Robotics #LineFollowerRobot #Arduino #PIDControl #EmbeddedSystems #Electronics #RoboticsEngineering #DIYRobotics #EngineeringStudent #TechInnovation

HThis is our ultrasonic obstacle-avoidance robot car.What you see in the photos is our current prototype sample, with a custom 3D-printed shell. It carries an HC-SR04 ultrasonic sensor on an SG90 servo mount, which scans surroundings to detect and avoid obstacles.Important note:The 3D printed sample shell is only for rapid design verification. It has limited structural rigidity, prone to deformation and imperfect assembly fit. The surface finish and fit quality of this prototype are not representative of our final product.For mass production, we will switch to an aluminum alloy housing.The aluminum shell delivers much better structural strength to avoid deformation, tighter assembly tolerances, cleaner surface finish, and even reduces the overall weight of the robot.This is still an ongoing design iteration. Let me know if you have any questions!

In a couple of months, I’ll be 17 years old.

And recently, I came up with the idea of creating my own Robot. With artificial intelligence, so that perhaps I could create something similar to a personality, like humans have.

Right now, I’m learning C++, and I have a small plan of what else I still need to study in order to create something like that. (biology, physics, chemistry, engineering, robotics, psychology).

The idea is to create something very similar to a human. emotions, feelings, and something similar. and to create something like that, I thought about programming hormones.

I’m writing this here to get some advice on what else I need to study. or to get warnings that it will be very difficult to recreate.

P.S. sorry for my English, I'm using Google translate. I'm from Russia, if it's important (I hope it won't cause me any problems). First time I posted something on Reddit

So, after getting tired of training and testing robot policies on animated simulations which never translated well on real hardware, we decided its time to build photo-real simulation environment without waiting the tech giants to make it happen.

The best approach we've found is to build high quality Gaussian Splats of real sites (this is from our office) and make it augmentable, and relightable.

We're combining Splats and Meshes in Physics environment to build a realistics version of real places:

- which looks as real as the real world,
- gives us the same physics currently possible in any mesh environment
- and allow us to create 100s of variations of the same environment for domain variations.

We've built a pipeline after 100s of iterations, which converts an iphone scan of the site, to a SPLAT + meshes, and lets you choose the assets you want manipulatable with robots. It then builds the detailed assets based on supposed relaistic behaviours of that asset, by breaking it down into units and places that asset into the same position in the SPLAT for robot manipulation.

We're using Mujoco Wasm for physics and renderring the SPLATs inside mujoco. Robot used is Franka Panda.

Happy to share more details and our stack with others who need this and open to learn how others are solving this for their robots.

Boston Dynamics connected standard electric-scooter wheels directly to Atlas’ ankle actuators using a single custom adapter, requiring no other major hardware modifications.

The experiment was designed to stress the robot’s motors at high torque and rotational speeds while testing whether reinforcement-learning controllers trained in simulation could transfer successfully to physical hardware. Engineers refined their simulated motor models using measurements from the real actuators, helping Atlas reproduce movements such as sideways dashes.

The 360-degree jump used human motion data and reportedly succeeded on its first physical attempt, although Atlas adjusted the movement by rolling its lower body into position before takeoff.

This wheeled Atlas is a research platform rather than a planned product. Could hybrid humanoids that switch between walking and rolling eventually prove more practical than robots designed around legs alone?