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Ever wondered how engineers model ride comfort? This 2‑DOF quarter‑car simulation compares passive vs active suspension under road excitation — a classic problem in vehicle dynamics and control. From theory → simulation → insight 💡 🔗

MATLAB

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𝗣𝗼𝗽𝘂𝗹𝗮𝗿 𝗼𝗽𝗶𝗻𝗶𝗼𝗻: "𝗝𝘂𝘀𝘁 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲 𝗺𝗼𝗿𝗲 𝘀𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗱𝗮𝘁𝗮." After working with many 𝗿𝗼𝗯𝗼𝘁 𝗺𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 teams who've fallen into the simulation trap, here's what I've learned: Simulation teaches your robot to be really, really good at simulation. Unlike blind locomotion policies that can get away with sim-to-real transfer because they rely mainly on proprioception and contact forces, 𝘃𝗶𝘀𝗶𝗼𝗻-𝗴𝘂𝗶𝗱𝗲𝗱 𝗺𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝗲𝘅𝘁𝗿𝗲𝗺𝗲𝗹𝘆 𝘀𝗲𝗻𝘀𝗶𝘁𝗶𝘃𝗲 𝘁𝗼 𝘃𝗶𝘀𝘂𝗮𝗹 𝗱𝗼𝗺𝗮𝗶𝗻 𝗴𝗮𝗽. The subtle differences accumulate: - Simulated friction vs real surface textures - Perfect lighting vs shadows, reflections, glare - Ideal object geometries vs manufacturing tolerances - Instantaneous sensor readings vs real-world noise and latency - Clean backgrounds vs cluttered, dynamic environments 𝗧𝗵𝗲 𝗰𝗹𝗮𝘀𝘀𝗶𝗰 𝗽𝗿𝗼𝗴𝗿𝗲𝘀𝘀𝗶𝗼𝗻: Week 1: "Our model works perfectly in sim!" Week 2: "Let's collect some real data to fine-tune." Week 3: "The real data completely contradicts what the sim taught..." Week 4: "Okay, let's collect way more real data." Month 2: "We basically need to retrain from scratch." 𝗧𝗵𝗲 𝗽𝗮𝗶𝗻𝗳𝘂𝗹 𝘁𝗿𝘂𝘁𝗵: There's no shortcut to real-world data collection for vision-based manipulation. Simulation is amazing for debugging, prototyping, safety testing, and of course to supplement your real data. But it's not a substitute for understanding how your robot actually behaves in the actual environment. 𝗪𝗵𝗮𝘁 𝘄𝗼𝗿𝗸𝘀: Use simulation strategically - for exploring edge cases, testing safety boundaries, and rapid iteration. But build your production models on real data from real environments. The teams that succeed treat simulation as a powerful tool, not a magic solution. This is why Neuracore focuses on making real-world data collection so much easier and faster. Because the physics of your actual environment can't be simulated away. 𝗪𝗼𝗿𝗹𝗱 𝗺𝗼𝗱𝗲𝗹𝘀, 𝘆𝗼𝘂 𝘀𝗮𝘆? 𝗪𝗲𝗹𝗹, 𝗽𝗲𝗿𝗵𝗮𝗽𝘀 𝗺𝗼𝗿𝗲 𝗼𝗻 𝘁𝗵𝗮𝘁 𝗶𝗻 𝗮𝗻𝗼𝘁𝗵𝗲𝗿 𝗽𝗼𝘀𝘁! 𝗪𝗵𝗮𝘁'𝘀 𝗯𝗲𝗲𝗻 𝘆𝗼𝘂𝗿 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝘄𝗶𝘁𝗵 𝘀𝗶𝗺-𝘁𝗼-𝗿𝗲𝗮𝗹 𝘁𝗿𝗮𝗻𝘀𝗳𝗲𝗿? 𝗛𝗮𝘀 𝗶𝘁 𝘄𝗼𝗿𝗸𝗲𝗱 𝗮𝘀 𝘄𝗲𝗹𝗹 𝗮𝘀 𝗲𝘅𝗽𝗲𝗰𝘁𝗲𝗱?

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Around 8:55 am on Boxing Day 26th December 2025, as I was coming back from my night duty, I saw this car doing like 80-90 miles/hr on a 60 mile/hr road. Temperature was 1 degree Celsius and roads were icy. I was worried because that road has loads of bends and it was crazy to see someone speeding like that on that road. Not up to 3 minutes, this chap approaching a bend suddenly went on his brakes, then lost control as the car started skidding. To our left is a hill, and beyond this hill is a river. This guy climbed that hill with speed. He drove on it for like 5 seconds while trying to re-establish control of the car, then the car came down and he struggled for another 3 seconds and then regained control, he sped off and continued driving. By this time, I had slowed down and was observing what was happening as I was just behind him. The broken parts of his car littered the road but this dude continued driving and speeding. This got me worried, he had a near death experience, every normal person would stop, park and soak in whatever that happened, and most especially, see his car and the damage done. This guy continued speeding like a mad man. I couldn’t call police because I was driving and not allowed to touch my phone, but I was dead worried this dude might be driving a stolen car ( because how do you smash your car in this economy and not park to even see the damage?). The tyre might be damaged and if he continues speeding like that, can have a tyre burst and crash into on coming vehicle. So I made up my mind to follow him. I started flashing lights, he noticed and slowed down, then I went close but he sped off again. I followed him again and continued flashing lights. I was just policing him until he parked and I double crossed him and had a go at him. I sha called the police and passed his details to him. So I’m posting the plate number in case someone stole your car, definitely must be this guy!! Contact police, they have the details and the area the incident took place.

Around 8:55 am on Boxing Day 26th December 2025, as I was coming back from my night duty, I saw this car doing like 80-90 miles/hr on a 60 mile/hr road. Temperature was 1 degree Celsius and roads were icy. I was worried because that road has loads of bends and it was crazy to see someone speeding like that on that road. Not up to 3 minutes, this chap approaching a bend suddenly went on his brakes, then lost control as the car started skidding. To our left is a hill, and beyond this hill is a river. This guy climbed that hill with speed. He drove on it for like 5 seconds while trying to re-establish control of the car, then the car came down and he struggled for another 3 seconds and then regained control, he sped off and continued driving. By this time, I had slowed down and was observing what was happening as I was just behind him. The broken parts of his car littered the road but this dude continued driving and speeding. This got me worried, he had a near death experience, every normal person would stop, park and soak in whatever that happened, and most especially, see his car and the damage done. This guy continued speeding like a mad man. I couldn’t call police because I was driving and not allowed to touch my phone, but I was dead worried this dude might be driving a stolen car ( because how do you smash your car in this economy and not park to even see the damage?). The tyre might be damaged and if he continues speeding like that, can have a tyre burst and crash into on coming vehicle. So I made up my mind to follow him. I started flashing lights, he noticed and slowed down, then I went close but he sped off again. I followed him again and continued flashing lights. I was just policing him until he parked and I double crossed him and had a go at him. I sha called the police and passed his details to him. So I’m posting the plate number in case someone stole your car, definitely must be this guy!! Contact police, they have the details and the area the incident took place.

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757,329 görüntüleme • 9 ay önce

A Letter to Our Community: The Road Ahead for Robotics To our Community and Partners, As we step into 2026, our mission at Axis is clearer than ever: Constructing the definitive End-to-End Scaling Layer for Robotics. Our goal is to accelerate the transfer of diverse human intelligence into Robotics General Intelligence (RGI). By owning the critical path of intelligence creation, we are turning the physical limitations of robotics into a scalable, software-driven future. Here is our strategic outlook and roadmap for the year ahead. The Core Thesis: Simulation is the Only Way Out The path to RGI is currently blocked by Data Scarcity, Generalization Fragility, and Hardware Fragmentation. At Axis, we believe Simulation is the only way out. Our Simulation Data Platform and Data Augmentation Engine transform raw data into "Synthetic Gold". Backed by academic milestones like Roboverse, Skill Blending, and GraspVLA, we have proven that pure simulation can achieve the generalization required for the real world. We don’t just collect data; we architect it. The Engine: Why Crypto? We believe RGI should come from all, not a few. Crypto is not just a feature; it is the primitive that powers our entire ecosystem flywheel: - Incentive Mechanism: Democratizing contribution and rewarding the trainers and developers. - Assetization: Turning proprietary data and refined models into liquid, ownable assets. - Verifiable Workflow: We are opening the "Black Box" of AI. By bringing total transparency to the Task Generation → Data Collection → Model Training pipeline, we ensure every byte of intelligence is verifiable, traceable, and secure. 2026 Strategic Deliverables This year, we are committed to delivering three foundational pillars: - The World's Largest Training Dataset for Robots: A robot training set—diverse, high-quality interaction data at an unprecedented scale. - A Robotics Foundation Model: A universal robotic brain trained on our pure simulation and synthetic data, capable of robust cross-embodiment transfer and open-world adaptability. - Evolvable Robot Hardware: Robots deployed with Axis models that autonomously evolve through continuous interaction, turning every deployment into a self-improving node within our RGI network. The Ultimate Vision We are building more than models; we are architecting the Distributed Machine Economy. A future where every dataset, model, and robotic embodiment is a verifiable asset in a global, autonomous network. Thank you for building the future of intelligence with us✌️📷

A Letter to Our Community: The Road Ahead for Robotics To our Community and Partners, As we step into 2026, our mission at Axis is clearer than ever: Constructing the definitive End-to-End Scaling Layer for Robotics. Our goal is to accelerate the transfer of diverse human intelligence into Robotics General Intelligence (RGI). By owning the critical path of intelligence creation, we are turning the physical limitations of robotics into a scalable, software-driven future. Here is our strategic outlook and roadmap for the year ahead. The Core Thesis: Simulation is the Only Way Out The path to RGI is currently blocked by Data Scarcity, Generalization Fragility, and Hardware Fragmentation. At Axis, we believe Simulation is the only way out. Our Simulation Data Platform and Data Augmentation Engine transform raw data into "Synthetic Gold". Backed by academic milestones like Roboverse, Skill Blending, and GraspVLA, we have proven that pure simulation can achieve the generalization required for the real world. We don’t just collect data; we architect it. The Engine: Why Crypto? We believe RGI should come from all, not a few. Crypto is not just a feature; it is the primitive that powers our entire ecosystem flywheel: - Incentive Mechanism: Democratizing contribution and rewarding the trainers and developers. - Assetization: Turning proprietary data and refined models into liquid, ownable assets. - Verifiable Workflow: We are opening the "Black Box" of AI. By bringing total transparency to the Task Generation → Data Collection → Model Training pipeline, we ensure every byte of intelligence is verifiable, traceable, and secure. 2026 Strategic Deliverables This year, we are committed to delivering three foundational pillars: - The World's Largest Training Dataset for Robots: A robot training set—diverse, high-quality interaction data at an unprecedented scale. - A Robotics Foundation Model: A universal robotic brain trained on our pure simulation and synthetic data, capable of robust cross-embodiment transfer and open-world adaptability. - Evolvable Robot Hardware: Robots deployed with Axis models that autonomously evolve through continuous interaction, turning every deployment into a self-improving node within our RGI network. The Ultimate Vision We are building more than models; we are architecting the Distributed Machine Economy. A future where every dataset, model, and robotic embodiment is a verifiable asset in a global, autonomous network. Thank you for building the future of intelligence with us✌️📷

Axis Robotics

28,096 görüntüleme • 9 ay önce

THE TESLA MODEL S: THE CAR THAT MADE ELECTRIC VEHICLES SERIOUS When the Model S launched in 2012, the entire world still saw EVs as slow, boring, short-range toys for tree-huggers. The Model S changed that narrative overnight. It wasn’t just an electric car — it was a statement. Here’s why the Model S was so important for EV adoption: • It proved EVs could be faster and better than gas cars 0–60 mph in under 4 seconds (later Plaid versions under 2 seconds) while being completely silent and smooth. It beat most supercars off the line and made “electric” synonymous with performance. • It delivered real long-range capability Over 300 miles of range when most EVs at the time struggled to reach 100 miles. Suddenly, road trips became possible and “range anxiety” started to feel outdated. • It introduced over-the-air updates The first production car that could get major performance upgrades, new features, and safety improvements wirelessly — like a smartphone on wheels. This changed how people think about car ownership forever. • It forced the entire auto industry to respond Legacy manufacturers who had been dragging their feet on EVs suddenly rushed to catch up. The Model S basically lit the fuse for the modern EV revolution. • It made luxury electric desirable Premium interior, massive touchscreen, ridiculous acceleration, and futuristic design turned EVs from “compromise” into “aspiration.” Without the Model S proving that electric cars could outperform and out-luxury gasoline vehicles, we wouldn’t have the Model 3/Y explosion, the Cybertruck, or the flood of competitors now racing to go electric. The Model S didn’t just sell cars. It changed the future of transportation. It took EVs from niche to mainstream and showed the world what was possible.

THE TESLA MODEL S: THE CAR THAT MADE ELECTRIC VEHICLES SERIOUS When the Model S launched in 2012, the entire world still saw EVs as slow, boring, short-range toys for tree-huggers. The Model S changed that narrative overnight. It wasn’t just an electric car — it was a statement. Here’s why the Model S was so important for EV adoption: • It proved EVs could be faster and better than gas cars 0–60 mph in under 4 seconds (later Plaid versions under 2 seconds) while being completely silent and smooth. It beat most supercars off the line and made “electric” synonymous with performance. • It delivered real long-range capability Over 300 miles of range when most EVs at the time struggled to reach 100 miles. Suddenly, road trips became possible and “range anxiety” started to feel outdated. • It introduced over-the-air updates The first production car that could get major performance upgrades, new features, and safety improvements wirelessly — like a smartphone on wheels. This changed how people think about car ownership forever. • It forced the entire auto industry to respond Legacy manufacturers who had been dragging their feet on EVs suddenly rushed to catch up. The Model S basically lit the fuse for the modern EV revolution. • It made luxury electric desirable Premium interior, massive touchscreen, ridiculous acceleration, and futuristic design turned EVs from “compromise” into “aspiration.” Without the Model S proving that electric cars could outperform and out-luxury gasoline vehicles, we wouldn’t have the Model 3/Y explosion, the Cybertruck, or the flood of competitors now racing to go electric. The Model S didn’t just sell cars. It changed the future of transportation. It took EVs from niche to mainstream and showed the world what was possible.

Tesla Owners Silicon Valley

11,056 görüntüleme • 6 ay önce

Who needs a gaming console when you can run driving simulations with Simulink 😎🚦 Learn how:

Who needs a gaming console when you can run driving simulations with Simulink 😎🚦 Learn how:

MATLAB

11,347 görüntüleme • 1 yıl önce

Breaking news 🗞️ 🚨 Tesla just quietly solved a problem in Australia. The Model X is gone from our market. But the new Model Y L Premium AWD might actually be the closest thing we have to a replacement. And honestly… it makes a lot of sense. ⚡ Tesla Model Y L – Key Specs • 0–100 km/h: ~5.0 sec • Range: ~681 km WLTP • Top speed: 201 km/h • Seating: 6 adults • Supercharging: 250 kW • ~288 km added in 15 min 💰 Australian pricing (before on-road costs) Model Y Long Range AWD → $68,900 Model Y L Premium AWD → ~$74,900 So for roughly $6k more, you get: ✔ 3 rows ✔ 6 seats ✔ Much larger cabin ✔ ~400L extra cargo capacity ✔ Longer wheelbase ✔ Even more range 📊 Quick comparison Model Y Long Range AWD • 5 seats • ~600 km range • 0–100 km/h: 4.8 sec • $68,900 Model Y L Premium AWD • 6 seats • ~681 km range • 0–100 km/h: 5.0 sec • ~$74,900 So performance drops slightly, but practicality goes way up. 🇦🇺 Why this matters in Australia Since Tesla stopped selling the Model X locally, there has been a real gap in the lineup for larger families. The Model Y L doesn’t completely replace the X. You lose things like: ❌ Adaptive air suspension ❌ Driver instrument cluster ❌ Falcon Wing doors ❌ Some luxury interior touches But you still get: ✔ Tesla software ecosystem ✔ Supercharger network ✔ Massive range ✔ Practical 3-row seating And at a much lower price than a Model X ever was. 👨‍👩‍👧‍👦 Who this is perfect for • Growing families • Current Model Y owners needing more space • Former Model X buyers • Anyone considering EV9 / EX90 but wanting Tesla’s ecosystem Personally, as a Model X owner, this is the first Tesla sold in Australia that actually feels like a realistic successor. I’m seriously considering replacing my Model X with the Model Y L, possibly around the end of Q2 or mid-Q3 this year. Not a perfect Model X replacement. But for Australia right now? This might be Tesla’s smartest family vehicle yet. ⚡🇦🇺 ORDER NOW : Tesla Australia & New Zealand Tesla AI

Breaking news 🗞️ 🚨 Tesla just quietly solved a problem in Australia. The Model X is gone from our market. But the new Model Y L Premium AWD might actually be the closest thing we have to a replacement. And honestly… it makes a lot of sense. ⚡ Tesla Model Y L – Key Specs • 0–100 km/h: ~5.0 sec • Range: ~681 km WLTP • Top speed: 201 km/h • Seating: 6 adults • Supercharging: 250 kW • ~288 km added in 15 min 💰 Australian pricing (before on-road costs) Model Y Long Range AWD → $68,900 Model Y L Premium AWD → ~$74,900 So for roughly $6k more, you get: ✔ 3 rows ✔ 6 seats ✔ Much larger cabin ✔ ~400L extra cargo capacity ✔ Longer wheelbase ✔ Even more range 📊 Quick comparison Model Y Long Range AWD • 5 seats • ~600 km range • 0–100 km/h: 4.8 sec • $68,900 Model Y L Premium AWD • 6 seats • ~681 km range • 0–100 km/h: 5.0 sec • ~$74,900 So performance drops slightly, but practicality goes way up. 🇦🇺 Why this matters in Australia Since Tesla stopped selling the Model X locally, there has been a real gap in the lineup for larger families. The Model Y L doesn’t completely replace the X. You lose things like: ❌ Adaptive air suspension ❌ Driver instrument cluster ❌ Falcon Wing doors ❌ Some luxury interior touches But you still get: ✔ Tesla software ecosystem ✔ Supercharger network ✔ Massive range ✔ Practical 3-row seating And at a much lower price than a Model X ever was. 👨‍👩‍👧‍👦 Who this is perfect for • Growing families • Current Model Y owners needing more space • Former Model X buyers • Anyone considering EV9 / EX90 but wanting Tesla’s ecosystem Personally, as a Model X owner, this is the first Tesla sold in Australia that actually feels like a realistic successor. I’m seriously considering replacing my Model X with the Model Y L, possibly around the end of Q2 or mid-Q3 this year. Not a perfect Model X replacement. But for Australia right now? This might be Tesla’s smartest family vehicle yet. ⚡🇦🇺 ORDER NOW : Tesla Australia & New Zealand Tesla AI

Tesla in the Gong 🇦🇺🦘🤖🚕

21,519 görüntüleme • 7 ay önce

The three-body problem is a classic and notoriously difficult question in physics and mathematics. It asks: How do three objects, such as stars, planets, or moons, move under the influence of each other’s gravity? Unlike the simpler two-body problem, which has precise and predictable analytical solutions (like the Earth orbiting the Sun in an ellipse), the three-body problem quickly becomes chaotic and unpredictable. This complexity arises because each object's motion constantly affects, and is affected by, the other two. These gravitational interactions form a tangled and unstable system. In fact, there's no general formula that can solve all three-body scenarios exactly. This was first demonstrated in the 19th century by Henri Poincaré, whose work laid the foundations for chaos theory. While exact solutions remain elusive, scientists have discovered certain special cases where the motion is stable or periodic. One well-known example is the Lagrange points, where three bodies can maintain a stable triangular configuration. However, such neat solutions are rare. Today, thanks to powerful computers, researchers can simulate three-body systems with remarkable accuracy, helping us study triple-star systems, exoplanets, and asteroid dynamics. Yet even small changes in the starting conditions can lead to dramatically different outcomes, highlighting the sensitive dependence on initial conditions that defines chaotic systems. The three-body problem is actually a specific case of the broader n-body problem, where n can be any number of interacting bodies. As n increases, the complexity and unpredictability rise even further. The three-body problem serves as a vivid example of how simple laws of nature, like Newton’s law of gravity, can produce behavior that is intricate, unexpected, and profoundly difficult to predict.

The three-body problem is a classic and notoriously difficult question in physics and mathematics. It asks: How do three objects, such as stars, planets, or moons, move under the influence of each other’s gravity? Unlike the simpler two-body problem, which has precise and predictable analytical solutions (like the Earth orbiting the Sun in an ellipse), the three-body problem quickly becomes chaotic and unpredictable. This complexity arises because each object's motion constantly affects, and is affected by, the other two. These gravitational interactions form a tangled and unstable system. In fact, there's no general formula that can solve all three-body scenarios exactly. This was first demonstrated in the 19th century by Henri Poincaré, whose work laid the foundations for chaos theory. While exact solutions remain elusive, scientists have discovered certain special cases where the motion is stable or periodic. One well-known example is the Lagrange points, where three bodies can maintain a stable triangular configuration. However, such neat solutions are rare. Today, thanks to powerful computers, researchers can simulate three-body systems with remarkable accuracy, helping us study triple-star systems, exoplanets, and asteroid dynamics. Yet even small changes in the starting conditions can lead to dramatically different outcomes, highlighting the sensitive dependence on initial conditions that defines chaotic systems. The three-body problem is actually a specific case of the broader n-body problem, where n can be any number of interacting bodies. As n increases, the complexity and unpredictability rise even further. The three-body problem serves as a vivid example of how simple laws of nature, like Newton’s law of gravity, can produce behavior that is intricate, unexpected, and profoundly difficult to predict.

Erika 

216,814 görüntüleme • 1 yıl önce