c/robotics

Four-legged robots can reach many places that wheeled vehicles cannot. Isn’t it a bit of a waste to treat them as mere means of transportation when they can carry loads weighing several metric tons? Their current speed is still a bit too slow—is this due to safety restrictions, or are the hardware limitations—such as the motors and batteries—preventing them from going faster? submitted by /u/D1n0saurMecha [link] [Kommentare]

I'm doing robotics work on an M4 MacBook Air. I have a task to simulate and automate a robot, but I'm running into major performance issues and crashes using Gazebo inside an Ubuntu VM via UTM. ​The bot renders fine at first, but whenever I try loading complex world terrains, Gazebo completely crashes. It seems like the virtualized GPU/hardware constraints are killing it. ​Is there a more efficient setup or workflow to run robotics simulations natively or smoothly on Apple Silicon? Would love to hear how other Mac users handle ROS/Gazebo! submitted by /u/Risheyyy [link] [Kommentare]

Awesome test overall!! Mind is running on mqtt Llama.app server with Qwen 3 model. Does what do you see and failure recovery (best solutions persisted) both on rover and arm approaches. submitted by /u/Additional-Buy2589 [link] [Kommentare]

I need to transfer a lot of force through this keyway into a 3d print, and am confused on the intended way to attach to this shaft. submitted by /u/IntroductionNo1700 [link] [Kommentare]

Am currently building a RC tank for a hobby project that wants to implement VSlam. Because of power constraints I want to use low power microcontrollers like esp32-cam and stream video to a laptop that then computes the navigation data. The idea being the ESP32 cam will upload IMU+stereo camera data -> Laptop computes current path and location -> Streams back navigation instructions. This doesnt have to be completely real time, as the robot can wait until a navigation solution is computed, execute the solution, stream back then wait for further instructions. My question is are there better ways to do something similar? Accuracy is the most important quality here. Or would a Lidar soluation be better? submitted by /u/FollowingHumble8983 [link] [Kommentare]

I’m building Haga, an independent physics-consistency checker for generated video and robot-policy simulations. An earlier CogVideoX-5b I2V experiment produced a clear failure mode: on a “ball and block fall” prompt, the tracked object stayed airborne with near-zero motion instead of falling. But that first result was post-hoc. I inspected those six clips before adding the static_hover detector, so the original 6/6 flag rate could not be treated as confirmation. I’ve now run a pre-registered held-out test. Method: Model: THUDM/CogVideoX-5b-I2V Cohort: 3 perspectives × seeds 2, 3 and 4 n=9 clips Detector thresholds and inclusion rules frozen before generation RGB → CoTracker3 → position-only VIDEO_CHECKS Discovery seeds 0–1 kept separate from held-out seeds 2–4 Result: Held-out flag rate: 1.000 (9/9) Wilson 95% CI: [0.701, 1.000] All nine clips fired static_hover Real Physics-IQ footage stayed quiet under the same profile static_hover fires when the tracked object remains airborne for most of the clip, has near-zero frame-to-frame speed, and does not exhibit gravitational acceleration. Important limitations: One open I2V model One ball-and-block-fall scene family One documented failure mode Real negative-control n=1 in this specific report Not Cosmos, Genie or NIM Not a broad claim about CogVideoX quality Write-up: https://haga.mushoodhanif.com/article/sim-physics-consistency-v1#held-out Lab: https://haga.mushoodhanif.com/lab/physicsiq Bounded demo: https://haga.mushoodhanif.com/demo I’d especially value criticism on: Which physical violations will position-only tracking systematically miss? Is static_hover defined narrowly enough to avoid confusing intentional suspension with failed dynamics? What public generated-video artifact should I evaluate next under the frozen detector? submitted by /u/Divine-Demon7 [link] [Kommentare]

Hey everyone! I’m a high school student helping run a student-led program that teaches Autodesk Fusion and CAD to students for free. We recently secured an international partnership and are getting ready to work with a lot more students, so we’re looking for a few more people to join the team. We’re especially hoping to find people who already have experience with CAD, whether that’s Autodesk Fusion, Onshape, SolidWorks, Inventor, or another program. Fusion experience would be ideal, but familiarity with other CAD software is still very useful since many of the main concepts carry over. The main roles we need are: Co-President and Vice Presidents: Help lead the team, communicate with partners, organize meetings, and help decide where the program goes next. This role will collapse onto the other two roles below. Mentors: Join weekly Zoom classes, demonstrate Fusion tools, answer questions, and help students when they get stuck. Curriculum Developers: Help improve our current lessons and create new activities, projects, and assignments. CAD experience is especially important for mentors and curriculum developers, but we’re also looking for people who are reliable, communicate well, and genuinely want to help students learn engineering. Apply here: https://docs.google.com/forms/d/e/1FAIpQLSckr1UBILkgySbmjvRhKD0qca_-Omxy_aLmG5aN6JIEhE9tJg/viewform?usp=dialog submitted by /u/Intelligent-Self1001 [link] [Kommentare]

I'm 15 years old and this is my hexapod project I have been working on for the past year, I learned a ton from it. Here are its specs: -Build: Mostly 3D printed, I used a model from Aecert Robotics from youtube, I made some changes and improvements to the model such as the femur joints that connect to the servos. -Parts: 24 channel Pololu maestro board, 11.4v lipo battery, 12x25kg servos, and 6x35kg servos (for the femur joints because they're under the most load). Cheap android phone for the controller and gyroscope, and a DROK buck converter. -Software: I made a custom android app for the controller that connects via wifi or hotspot, you scan a QR code and it opens the controller on your phone. I used inverse kinematic equations for the hexapod so it has complete control over the leg and body movement. -Stabilizing: Using the gyroscope from the phone it can also self stabilize, it can even walk and self stabilize at the same time. -Walking gait: There are 5 walking gaits so far: Tripod, ripple, wave, triple, and a custom one I made to look like a spider. -I'm currently working on a high precision robot arm and I would love some feedback: About 4ft long and hopefully can lift around 5lb. I should have some videos soon. If you want to learn more about the hexapod or the arm you can see them at my portfolio. submitted by /u/Safe_Tone1529 [link] [Kommentare]

Hi everyone, I just uploaded my first tutorial video on YouTube and wanted to share it here to get your opinions about it. its very short and simple tutorial for the subject matter but I figured since I shared my scripts anyone who is interested would like consult an Ai chatbot for their specific questions and the main point of the video is the briefly explain the main concepts and how it all works within PyBullet. if you have free 7 minutes, I would appreciate your thought and opinions about the video so I can improve for upcoming videos. I know Genetic Algorithms are a bit yesteryears news but I remember watching a video about them on 2minutespapers YouTube channel years ago and since the moment I loaded my robot to PyBullet I wanted to try to implement the technique myself on my own project. Thats why its the subject of my first tutorial video. I am also sharing the links to my GitHub repo for the scripts here as well in case if you dont want to watch the video but still interested in implementing genetic algorithm for robotics in PyBullet. PyBullet Genetic Algorithm repo: https://github.com/serdarselimys/PyBullet-GeneticAlgorithm PyBullet HexaDog ZBD control repo: https://github.com/serdarselimys/HexaDogZBD-PybulletDemo For the next tutorial I am planning to cover Imitation Learning, again in PyBullet. Do you think thats an interesting subject?? I have been seeing a lot of videos on social media about manual laborers, mostly, textile workers are being made to wear POV cameras to capture their work to be used to train Neural Networks. I figured a tutorial explaining how digital movements are copied over to neural networks would be interesting. submitted by /u/Xerd-R [link] [Kommentare]

Researchers at the University of Toronto's Continuum Robotics Laboratory introduced CRAFT, a 3D-printed modular design library for tendon-driven continuum robots that allows a single robot to physically reconfigure its shape, stiffness, and degrees of freedom within minutes by snapping together six interchangeable modules. The same base robot was reconfigured into a long teleoperated probe for aircraft-wing inspection achieving 41% reduction in sag, a pipe-crawling robot capable of navigating 90-degree bends and 30-degree inclines, and a soft robotic hand that successfully cracked eggs with 85% accuracy. CRAFT eliminates the need to build entirely new robots for different tasks, replacing bespoke redesign with rapid modular composition. Credits: https://www.nature.com/articles/s44182-026-00107-x submitted by /u/Similar_Suit_3709 [link] [Kommentare]