https://humanoidgpt.org/updates Robot models are now tested in unseen homes and judged on safety, yet benchmarks still show wide gaps. These figures and dated updates show what progressed, what failed and how to read the claims. en Sun, 04 Oct 2026 12:00:00 GMT https://humanoidgpt.org/updates#2026-09-18-figure-s-helix-2-5-is-tested-in-30-unseen-homes-and-succeeds-56-of-th humanoidgpt.org:2026-09-18-figure-s-helix-2-5-is-tested-in-30-unseen-homes-and-succeeds-56-of-th Fri, 18 Sep 2026 12:00:00 GMT Milestone Figure tested its Helix 2.5 robot policy in 30 Bay Area homes it had never seen, on tidying toys, folding towels and making beds. Across 420 attempts with no partial credit, it succeeded 56% of the time, versus 9% without Figure's Index pretraining. Tidying scored lowest at 40%. Why it matters: A 44% miss rate shows why home-style pilots need measured success rates on your own tasks, not demo clips. Ask any vendor for trial counts, failure definitions and results from sites the robot has not seen. Source: humanoid.guide (https://humanoid.guide/?p=18222) https://humanoidgpt.org/updates#2026-09-02-safe-stop-paper-teaches-a-humanoid-to-judge-when-stopping-will-not-ma humanoidgpt.org:2026-09-02-safe-stop-paper-teaches-a-humanoid-to-judge-when-stopping-will-not-ma Wed, 02 Sep 2026 12:00:00 GMT Research Researchers posted a method that estimates whether a humanoid can still stop safely from its current motion, then falls back to another policy if it cannot. On a Unitree G1 in simulation it stopped successfully in 96.4% of 179,650 test starts, with 150 trials on hardware. Why it matters: Emergency stops on legged robots are not automatic. Ask humanoid vendors how their stop behavior was tested, from which motions, and how often real-world trials disagreed with simulation. Source: arXiv (https://arxiv.org/pdf/2609.02358) https://humanoidgpt.org/updates#2026-08-25-skild-ai-says-its-s1-model-learns-a-10-minute-task-from-one-human-vid humanoidgpt.org:2026-08-25-skild-ai-says-its-s1-model-learns-a-10-minute-task-from-one-human-vid Tue, 25 Aug 2026 12:00:00 GMT Launch Skild AI introduced S1, a robot model prompted with a single human video instead of retraining. It reports 66% per-step success on unseen tasks lasting up to 10 minutes, against 9% for language-prompted policies. The results come from Skild's own benchmarks, and S1 has no public weights or API yet. Why it matters: A model that learns from one video could shorten setup for site-specific jobs, but today's evidence is vendor-run and the model is not yet public. Ask for independent trials before planning around it. Source: Runtime Wire (https://runtimewire.com/article/skild-ai-s1-robot-model-one-video-prompt) https://humanoidgpt.org/updates#2026-06-26-libero-safety-tests-10-robot-ai-models-on-collisions-people-and-risky humanoidgpt.org:2026-06-26-libero-safety-tests-10-robot-ai-models-on-collisions-people-and-risky Fri, 26 Jun 2026 12:00:00 GMT Research A new benchmark scores ten vision-language-action models on five safety suites, from careful grasping to refusing hazardous instructions, using 19,664 collision-free demonstrations. Success fell sharply at the hardest level: OpenVLA managed 4.0% to 12.7%, and RoboBrain2.0's refusal rate dropped from 80% to 20%. Why it matters: Safety is measurable, and today's models degrade when scenes get harder. When a vendor cites an AI model, ask which safety tests it passed, at what difficulty, and whether results are public. Source: arXiv (https://arxiv.org/pdf/2606.23686) https://humanoidgpt.org/updates#2026-04-16-physical-intelligence-unveils-0-7-one-model-that-matches-specialists- humanoidgpt.org:2026-04-16-physical-intelligence-unveils-0-7-one-model-that-matches-specialists- Thu, 16 Apr 2026 12:00:00 GMT Research Physical Intelligence released π0.7, a general-purpose robot model that combines skills it learned separately to handle new tasks. The company says one model matches fine-tuned specialists on jobs like laundry folding and espresso making, and folded laundry on a two-arm UR5e robot it had no data for. Why it matters: One model that transfers between robot bodies would cut the cost of switching hardware. Treat cross-robot claims as research, and check reach and payload for the exact robot on its Spec Card at The Humanoid Group. Source: Physical Intelligence (https://pi.website/pi07) https://humanoidgpt.org/updates#2026-04-07-agibot-opens-its-world-2026-robot-dataset-including-failed-attempts-a humanoidgpt.org:2026-04-07-agibot-opens-its-world-2026-robot-dataset-including-failed-attempts-a Tue, 07 Apr 2026 12:00:00 GMT Launch AgiBot released the first phase of AGIBOT WORLD 2026, an open-source dataset of hundreds of hours of real-world robot data from homes and commercial spaces. It pairs camera, tactile, lidar and joint data with digital-twin simulations, and keeps annotated error-recovery trajectories from free-form teleoperation. Why it matters: Open datasets that include failures let smaller teams train and test models without building their own data pipeline. Check the license, which robot body the data came from, and whether it matches your hardware. Source: The Robot Report (https://www.therobotreport.com/agibot-world-2026-dataset-open-source-accelerate-embodied-ai-development/)