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Strike Robot

@StrikeRobot_ai • 4,228 subscribers

SR Agentic + SR Platform — Build the new normal for robots faster. 📃 https://t.co/mSwShTQQoB 📃 https://t.co/zrm7RXT3eP

Shorts

This is how Strike Robot turns Simulation into Reality! One of the biggest challenges in robotics is ensuring that behaviors validated in simulation work reliably in the real world. For this experiment, we reconstructed part of a real laboratory at Eastworlds inside SR Platform. The generated layout was then deployed into MuJoCo. Using SR Agentic, the robot was tasked with finding abnormal objects in a cluttered environment and sending a Telegram notification when detected. Before deployment, everything is validated in simulation.

This is how Strike Robot turns Simulation into Reality! One of the biggest challenges in robotics is ensuring that behaviors validated in simulation work reliably in the real world. For this experiment, we reconstructed part of a real laboratory at Eastworlds inside SR Platform. The generated layout was then deployed into MuJoCo. Using SR Agentic, the robot was tasked with finding abnormal objects in a cluttered environment and sending a Telegram notification when detected. Before deployment, everything is validated in simulation.

14,792 views

Spent a day in Hangzhou, China. Robotic landscape here is top-notch.

Spent a day in Hangzhou, China. Robotic landscape here is top-notch.

18,982 views

From seeing → to understanding → now to following. In the previous video, we showed how the robot sees and navigates the world. This time, we’ve upgraded SR Agentic — it can now identify a designated person and autonomously follow them in real-time. Powered by perception + reasoning + adaptive navigation, the robot doesn’t just react - it tracks intent and moves with purpose.

From seeing → to understanding → now to following. In the previous video, we showed how the robot sees and navigates the world. This time, we’ve upgraded SR Agentic — it can now identify a designated person and autonomously follow them in real-time. Powered by perception + reasoning + adaptive navigation, the robot doesn’t just react - it tracks intent and moves with purpose.

25,351 views

From seeing → to understanding → to following → now to finding. In the last update, our robot learned how to recognize and follow people SR Agentic now evolves from human-following → to goal-driven object search. Give it a task like: → “find the white bottle on the table ” It will: • break down the instruction via LLM task planning • scan the environment in real-time • localize the object in 3D space • navigate and approach autonomously Step by step, capability by capability — from perception → to tracking → to task execution in the physical world. This is how real-world agentic robotics is built

From seeing → to understanding → to following → now to finding. In the last update, our robot learned how to recognize and follow people SR Agentic now evolves from human-following → to goal-driven object search. Give it a task like: → “find the white bottle on the table ” It will: • break down the instruction via LLM task planning • scan the environment in real-time • localize the object in 3D space • navigate and approach autonomously Step by step, capability by capability — from perception → to tracking → to task execution in the physical world. This is how real-world agentic robotics is built

21,916 views

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This robot now carries its own brain — a Qualcomm Dragonwing™ QCS6490 mounted right on its back. No more waiting on the cloud to make sense of the world. Everything processed on the spot, in real time. That's SR Agentic at work.

This robot now carries its own brain — a Qualcomm Dragonwing™ QCS6490 mounted right on its back. No more waiting on the cloud to make sense of the world. Everything processed on the spot, in real time. That's SR Agentic at work.

28,344 views • 10 days ago

Creating a simulated world for robots has never been easier than now. Introduce SR Platform. SR Platform provides a seamless generation pipeline: • Asset Creation • Spatial Layout Generation • Real-time Editing • Simulation & Rollout Using every model. Data stay yours. Powered by Venice Try it:

Creating a simulated world for robots has never been easier than now. Introduce SR Platform. SR Platform provides a seamless generation pipeline: • Asset Creation • Spatial Layout Generation • Real-time Editing • Simulation & Rollout Using every model. Data stay yours. Powered by Venice Try it:

25,229 views • 14 days ago

Humanoid robotics is the next great labor shift — and the real opportunity is not in the hardware. Strike Robot is now live on Virtuals Protocol — we’re building SR Agentic, a plug-and-play agentic framework for robotics, starting with Unitree G1, enabling autonomous anomaly detection, safety monitoring, and continuous operation in complex environments. AI makes robots intelligent. $SR makes them investable. Every robot. Its own right. Our journey starts today.

Humanoid robotics is the next great labor shift — and the real opportunity is not in the hardware. Strike Robot is now live on Virtuals Protocol — we’re building SR Agentic, a plug-and-play agentic framework for robotics, starting with Unitree G1, enabling autonomous anomaly detection, safety monitoring, and continuous operation in complex environments. AI makes robots intelligent. $SR makes them investable. Every robot. Its own right. Our journey starts today.

100,774 views • 3 months ago

Hours of manual asset authoring => Down to 1–2 minutes with 1 prompt. SR Platform generates interactive, simulation-ready 3D assets for training robotics, complete with articulated objects and physics. Native support for MuJoCo and NVIDIA Isaac Sim. Coming in July!

Hours of manual asset authoring => Down to 1–2 minutes with 1 prompt. SR Platform generates interactive, simulation-ready 3D assets for training robotics, complete with articulated objects and physics. Native support for MuJoCo and NVIDIA Isaac Sim. Coming in July!

12,778 views • 12 days ago

/ NOTICE → / REASON → / DECIDE → / ACT The obstacle wasn't there before. It appeared mid-mission & the robot had under 200ms to notice, reason, and reroute. This run, we tested unexpected scenario detection and validated balance stability against our own trained policy. No hardcoded rules. No human input.

/ NOTICE → / REASON → / DECIDE → / ACT The obstacle wasn't there before. It appeared mid-mission & the robot had under 200ms to notice, reason, and reroute. This run, we tested unexpected scenario detection and validated balance stability against our own trained policy. No hardcoded rules. No human input.

28,485 views • 2 months ago

Testing image-to-CAD for SR Platform on a new set of GPUs 🔥 We are working with lium.io (SN51) to showcase the efficiency of decentralized compute for SR Platform — from CAD generation to RL training and sim-to-real validation What it means: > Flexible, on-demand rental for us. Pay with crypto. > Diverse GPU options, powered by Openτensor Foundaτion's incentive alignment. > Lower equipment cost → higher margin for the network. Onchain robots, onchain compute.

Testing image-to-CAD for SR Platform on a new set of GPUs 🔥 We are working with lium.io (SN51) to showcase the efficiency of decentralized compute for SR Platform — from CAD generation to RL training and sim-to-real validation What it means: > Flexible, on-demand rental for us. Pay with crypto. > Diverse GPU options, powered by Openτensor Foundaτion's incentive alignment. > Lower equipment cost → higher margin for the network. Onchain robots, onchain compute.

18,134 views • 1 month ago

Spent a day in Hangzhou, China. Robotic landscape here is top-notch.

Spent a day in Hangzhou, China. Robotic landscape here is top-notch.

18,982 views • 2 months ago

Safeguards need to know how to fight too. 🥋 Fast warmup before getting to work — at Eastworlds

Safeguards need to know how to fight too. 🥋 Fast warmup before getting to work — at Eastworlds

21,256 views • 3 months ago

This is how the robot sees the world — straight from its camera + LiDAR. A small use case of StrikeRobot Agentic, showing how agentic systems operate in real scenarios: • Detects the target person via edge-optimized face detection • Detects obstacles in real time • Estimates distance using camera physics (beyond depth sensor limits of Unitree G1) • Plans the shortest path with A* + smooth trajectories using Bezier • Continuously replans as the environment changes ✅ Result: the robot avoids obstacles, optimizes its path, and autonomously moves toward the designated person.

This is how the robot sees the world — straight from its camera + LiDAR. A small use case of StrikeRobot Agentic, showing how agentic systems operate in real scenarios: • Detects the target person via edge-optimized face detection • Detects obstacles in real time • Estimates distance using camera physics (beyond depth sensor limits of Unitree G1) • Plans the shortest path with A* + smooth trajectories using Bezier • Continuously replans as the environment changes ✅ Result: the robot avoids obstacles, optimizes its path, and autonomously moves toward the designated person.

12,333 views • 3 months ago

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