c/robotics

Has anyone used one of these yet? They have been out a few months but I can't find much on YouTube or here about real world experience. I want to use one to pick individual bicycle spokes from a container and place into a V shaped trough. Spokes are 2mm diameter and about 300mm long. Any comments about the practicality of this? I'm most familiar with Python and assume I need a camera and AI / vision to pickup objects. The arm would need to trigger other equipment from a gpio. Does this mean the Jetson Nano option is the best option? submitted by /u/Illustrious_Ad_764 [link] [Kommentare]

I have a Borunte BRTIRUS0707A 6-axis arm (HC1 controller, F5.2.1 firmware) and there was no ROS 2 support for it, so I created one and put it on GitHub: 👉 https://github.com/rqtqp/ros2_borunte_0707A It's a ROS 2 (Humble) workspace that talks to the controller over its JSON-over-TCP interface (port 9760) — no vendor SDK needed. What works today: Telemetry — live joint state on /joint_states, plus controller status/health. MoveIt 2 motion — Plan + Execute in RViz actually moves the real arm (the bridge turns the planned trajectory into the controller's AddRCC motion command). Safety — dry-run by default, live precondition gate (mode/alarm/limits), soft limits, and a /stop abort service. Model (URDF + meshes) and a MoveIt config included, plus a documented mechanical-zero (groove/blade) home calibration. Sharing it in case it's useful to anyone working with these arms. If you have questions about this piece of equipment (the arm, the HC1 controller, or its remote-command protocol), feel free to ask 🙂 submitted by /u/tru0ne [link] [Kommentare]

So basically I'm using: Feetech SCS-15 Serial Servo motors Feetech FE-URT-2 USB to TTL Controller Voltage Regulator Module (5V output) Raspberry Pi 3.7v 18650 Batteries to control the servo motors in the daisy chain ish way. For some reason I need to power servos using batteries individually, and I am not sure how I could do the wirings. Like, are they even different from one another and which way is the most adequate? In my poor understandings the ground seems all connected regardless of which way of these 3. submitted by /u/Dangerous_Break5656 [link] [Kommentare]

We brought the robot world to Chicago. At Automate 2026, Faraday Future showcased our full EAI robot lineup on the show floor — humanoid, bionic, and mobile manipulator robots, powered by one brain across multiple forms. From the All-New Futurist to our new Faber mobile manipulator series, the FF EAI Robot World drew strong attendee traffic and major media coverage throughout the show. This is only the beginning of robots stepping into real-world life. Learn more: https://robotics.ff.com/us/ submitted by /u/FaradayFuture_FFAI [link] [Kommentare]

Ever since the post from last time: https://www.reddit.com/r/robotics/comments/1u1iql9/cubic_doggo_update_wobbly_imu/ I have tried to implement all the suggestions from the previous posts (thank you guys :)), and then spent way too much time tuning the PID, hoping it could perfectly balance the robot without wobbling. And the first video is showing my best full PID result so far: it can achieve perfect balance, BUT with randomly occurring spasms. A bubble level is added on its head. After standing+leveling, the platform is put on a slope. The bubble shifts, and the robot is trying to adjust it back Still cannot figure out the reason after quite some updates, though, but 50Hz reading rate with ~10ms lag, and legs lifting the whole body weight while changing tiny position probably are the culprit. So maybe it really doesn't need perfect leveling; it just needs some corrections on a slope. The second video is with P-only, fast reacting and no oscillation. Maybe this is showing the limitation of PID as compared to reinforcement learning? I am not at all sure. For now, though, I still want to see how P-only leveling performs during a walk gait. Link to the previous walking post without IMU: https://www.reddit.com/r/robotics/comments/1tghftd/cubic_doggo_full_github_record_it_can_now_walk/ submitted by /u/SphericalCowww [link] [Kommentare]

I’m attending the Automate Show in Chicago and tested the teleoperation solution on display at the Universal Robots booth. When it comes to physical intelligence, data collection is a critical component. Today the industry uses a variety of acquisition methods including VR systems and optical motion capture. Teleoperation remains a highly practical approach for data collection thanks to its reliability and intuitiveness. What do you think? submitted by /u/No_Challenge_3410 [link] [Kommentare]

I am building a perception pipeline from RGB-D for pick-and-place with a depth camera. The goal is to detect an object on a table, estimate its 3D position, and obtain a stable orientation that the robot can use to grasp it. In this post, I describe some things I learned during the first part of the implementation, after training the segmentation model: https://medium.com/@danieldoradotalaveron/getting-stable-yaw-for-robotics-pca-tabletop-and-the-beginning-of-my-tracking-pipeline-8b9dd3921d3a submitted by /u/nettrotten [link] [Kommentare]

As per Aditya Kamath (author): In this article, I discuss integrating a Luxonis OAK-D S2 stereo depth camera into my LeKiwi robot’s ROS 2 stack. I cover the steps I took to configure the depthai-ros driver to optimize bandwidth, simplify the URDF and launch files, and add pointcloud compression with Cloudini. I also discuss how I visualized RGB images, depth maps, and (compressed and uncompressed) pointclouds in Foxglove’s 3D panel, and the challenges I faced along the way. submitted by /u/arewegoing [link] [Kommentare]

Welcome to the latest RobotShift update, 5 stories with the take from demoware to reality. 00:00 - Intro 00:20 - The Architecture Shift — Duke’s Argus Why copying human form can be an efficiency trap. Duke University’s Argus is a 20-legged, 20-eyed sphere with no front or back, designed to move and see in any direction. Its 0.91 dynamic-isotropy score puts it far above conventional humanoid and legged designs for terrain such as sand, forests and obstacle-filled environments. 01:30 - Humanoid’s Outsourcing Strategy London-based Humanoid is taking a different route to scale: using established German industrial partners including Schaeffler and Bosch rather than building every part of its production ecosystem itself. The ambition is huge — but scaling hardware is very different from proving deployment. 02:37 - The Simulation Trap — Genesis AI GENE-26.5 demonstrates impressive manipulation tasks including egg cracking and lab pipetting. But impressive controlled demos still leave a difficult question: how much of that performance survives outside carefully managed environments, without extra algorithmic support? 03:44 - The Warehouse Bottleneck — Locus Robotics and Nexera Locus Robotics has acquired Nexera Robotics and its NeuraGrasp adaptive membrane-gripper technology. The target is clear: picking the messy, variable stock that warehouse robots still struggle with. Even tiny pick-failure rates can create thousands of expensive human exceptions at scale. 04:58 - Mass Scale Unlocked — Electric Atlas Hyundai and Boston Dynamics are building toward industrial-scale Atlas production and deployment in Georgia. The long-term ambition is a production system capable of around 30,000 robot units annually — a major test of whether humanoids can move from impressive demonstrations into repeatable factory economics. 06:04 - End Summary submitted by /u/ButterscotchTiny1114 [link] [Kommentare]

If it does not exist in real life and instead of the humanoids does it mean it didn't had the actual physics or it was just fiction? submitted by /u/ForsakenQuantity7294 [link] [Kommentare]

Check the FF (Nasdaq: $FFAI)'s EAI robot "super group" at Automate 2026 — North America's largest robotics show. submitted by /u/FaradayFuture_FFAI [link] [Kommentare]