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Axis Product Update The Precision & Security Patch is here. - Hardened Anti-Cheat: Deployed backend trajectory replay verification and end-state DB checks. Bots and invalid runs are strictly filtered. - Wrist-Cam View: Added a direct camera feed from the robot's wrist for precise manipulation. - Custom Sensitivity: A new...

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Axis Robotics

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18,667 görüntüleme • 3 ay önce •via X (Twitter)

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wrist smoothness training progress, wrist stutters are getting less but still happen in-game at random times. The training has allowed me to use a higher sensitivity than usual in-game. I also added horizontal/vertical scen's. For example: Air Voltaic
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𝗪𝗵𝗮𝘁 𝗮𝗿𝗲 𝗿𝗼𝗯𝗼𝘁 𝘀𝗶𝗻𝗴𝘂𝗹𝗮𝗿𝗶𝘁𝗶𝗲𝘀? A six-axis industrial robot arm has - 3 𝘁𝘆𝗽𝗲𝘀 𝗼𝗳 𝗿𝗼𝗯𝗼𝘁 𝘀𝗶𝗻𝗴𝘂𝗹𝗮𝗿𝗶𝘁𝘆 - 💡 Wrist singularities, elbow singularities, and shoulder singularities. 1️⃣ A wrist singularity occurs when the axes of joints 4 and 6 are coincident. 2️⃣ An elbow singularity occurs when the wrist center lies in the same plane as the axes of joints 2 and 3. 3️⃣ Finally, a shoulder singularity occurs when the wrist center lies in the plane passing through the axis of joint 1 and parallel to or passing through the axis of joint 2. Credit: Mecademic

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At Axis, every trajectory submitted by our community undergoes a strict replay validation process. We run each submission through checker to verify whether the target task was successfully completed. To see how strict it is, check this demo (Task: Place The Toy Train On The Board Game Box). Real human data passes smoothly (Video 1). However, bots or manually altered data will fail (Video 2). Why? Faking numbers breaks the simulation's physics causality. Even tiny tweaks cause error accumulation, resulting in failed movements. This invalid data is automatically rejected. Because of this mechanism, data submitted via bots will ultimately fail our replay verification. Invalid data is strictly excluded from model training, and the task slot is reopened to the community to collect genuine, high-quality trajectories. Furthermore, we actively monitor for duplicated data. Trajectories that are identical lack the diversity required for robot learning and will not be credited by our scoring system. If we detect accounts submitting a massive volume of identical trajectories, all associated addresses will be permanently banned. For Axis, the quality and diversity of data are the only ways to solve the robotics generalization gap. They will always be our absolute top priorities.

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Folks, here's another little design exercise that I spent the last few hours on 👍 This is based on a thesis I had for basically a decade now: Aiming in FPS games with the right analog stick is quite bad. Your thumb has maybe 1cm of travel on a tiny stick, fighting a spring, trying to make precise micro-adjustments AND fast 180-degree turns with the same input. If we're being honest, that's a terrible interface for the task. Your wrist, on the other hand, has roughly 180 degrees of rotational range, uses your entire forearm's muscle groups, and can make both ultra-precise micro-corrections and fast sweeping motions naturally. It's why mouse aiming destroys stick aiming: You're using your wrist and arm, not your thumb. So the thesis is simple: what if we just used wrist rotation directly as the aiming input? No VR headset, no special hardware. Just hold an old Switch1 Joy-Con in your right hand and rotate your wrist. Small rotations for precision tracking, larger rotations for fast turns. Recoil kicks the camera up and you instinctively tilt your hand back to compensate, etc. To me, it just feels right. I built a little prototype to test this. It has 4 weapons with some recoil, cover you can lean around, jump/crouch, lock-on targeting, ammo management, blablabla. The whole point is to see if this input method feels as good in practice as it does in theory. The aiming algorithm handles all the shitty stuff: Dead zones against shaky hands, auto-clutching when you unwind your wrist, asymmetric sensitivity because human wrists rotate further inward than outward, response curves for precision at low speed without sacrificing fast flicks, etc. I made a quick video to show the prototype in action. And if you wanna try it yourself, I put a small zip file up here that contains the executable:
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Folks, here's another little design exercise that I spent the last few hours on 👍 This is based on a thesis I had for basically a decade now: Aiming in FPS games with the right analog stick is quite bad. Your thumb has maybe 1cm of travel on a tiny stick, fighting a spring, trying to make precise micro-adjustments AND fast 180-degree turns with the same input. If we're being honest, that's a terrible interface for the task. Your wrist, on the other hand, has roughly 180 degrees of rotational range, uses your entire forearm's muscle groups, and can make both ultra-precise micro-corrections and fast sweeping motions naturally. It's why mouse aiming destroys stick aiming: You're using your wrist and arm, not your thumb. So the thesis is simple: what if we just used wrist rotation directly as the aiming input? No VR headset, no special hardware. Just hold an old Switch1 Joy-Con in your right hand and rotate your wrist. Small rotations for precision tracking, larger rotations for fast turns. Recoil kicks the camera up and you instinctively tilt your hand back to compensate, etc. To me, it just feels right. I built a little prototype to test this. It has 4 weapons with some recoil, cover you can lean around, jump/crouch, lock-on targeting, ammo management, blablabla. The whole point is to see if this input method feels as good in practice as it does in theory. The aiming algorithm handles all the shitty stuff: Dead zones against shaky hands, auto-clutching when you unwind your wrist, asymmetric sensitivity because human wrists rotate further inward than outward, response curves for precision at low speed without sacrificing fast flicks, etc. I made a quick video to show the prototype in action. And if you wanna try it yourself, I put a small zip file up here that contains the executable:

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📣 Meta Verified 📣 Meta Verified is a new subscription bundle that includes account verification with impersonation protections and access to increased visibility and support. More info here 👇🏼

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The latest Patch 1.08.00 for #CrimsonDesert added a new option to enable Ray Traced Shadows for sunlight and moonlight.
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The latest Patch 1.08.00 for #CrimsonDesert added a new option to enable Ray Traced Shadows for sunlight and moonlight.

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On 04/08/2024 at 6:30 PM EST, Marioiscool246 and I deployed 2 bots in an attempt to keep the last lobby on Nintendo Network alive. With a patch that kept us from disconnecting, we raced for over a month until Gears froze yesterday. Here is the beginning of the entire session.
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On 04/08/2024 at 6:30 PM EST, Marioiscool246 and I deployed 2 bots in an attempt to keep the last lobby on Nintendo Network alive. With a patch that kept us from disconnecting, we raced for over a month until Gears froze yesterday. Here is the beginning of the entire session.

Fishguy6564

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Another reason I’m interested in UMI style grippers is that tasks that‘d take 10s for a human take 5x as long with teleoperation. The lack of haptic and force feedback makes it hard to do movements relying on them like here, passing an object from one hand to another. Adding to that: teleoperation means you’re standing a meter away from the objects you’re operating on, and here for example, the box is obstructing the view of the PCBs. Thank you for great teleoperation Felix Neumann 🤝
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Another reason I’m interested in UMI style grippers is that tasks that‘d take 10s for a human take 5x as long with teleoperation. The lack of haptic and force feedback makes it hard to do movements relying on them like here, passing an object from one hand to another. Adding to that: teleoperation means you’re standing a meter away from the objects you’re operating on, and here for example, the box is obstructing the view of the PCBs. Thank you for great teleoperation Felix Neumann 🤝

Dominique Paul

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