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Summer Cammy low-res preview Another EEVEE test. I fixed the simulation issues and got a good workflow for working fast with this rig. Low-res render at only 16 samples. Besides the film grain/music, everything was done in Blender+EEVEE in realtime, including compositing/grade

164,539 görüntüleme • 4 ay önce •via X (Twitter)

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😓 Air India 🇮🇳 Flight AI171 with fully loaded Boeing 787-7 Dreamliner fatal accident: I‘m an airline pilot with >15‘000h of experience and a physics institute: My brief PRELIMINARY analysis of the visible facts from the video of the takeoff: * The flaps are only slightly extended, presumably to position 1 instead of 5. * The landing gear is still extended, which should have been retracted at this altitude and causes additional drag. * The aircraft is at a high angle of attack, which confirms the insufficient flap setting. * From the video and witness accounts, only low engine noise is audible. * Neither smoke nor fire is visible. * An engine failure is less likely. The most probable cause is presumably a human factor, an incorrectly chosen, insufficient flap setting for takeoff, and consequently an inadequately selected thrust. In this context, the correlated speeds were too low because they were calculated for a larger flap setting or a lighter aircraft. As a result, the aircraft took off with insufficient speed and intentionally but falsely derated thrust, was therefore on the unstable side, and rapidly lost more speed and altitude due to the additional failure to retract the landing gear in a timely manner, leading to a subsequent stall at low altitude and crash. For the experts: the aircraft got onto the wrong side of the speed vs drag curve and maneuvered itself into a corner from where there is no escape. Another possible cause could also have been an incorrect input of a wrong takeoff weight into the Flight Management System, resulting in too low thrust and too low speeds. The pilots got startled after takeoff, couldn’t wrap their head around what went wrong and incorrectly prioritized making an emergency call instead of flying the aircraft first, manually increasing thrust immediately to maximum, and retracting the landing gear. In summary of this very early and preliminary assessment (your confidence level should be as low as mine): The most probable cause is human error 😓 - as most of the time these days. Not because the pilots got worse (although that effect can be observed as well with prioritization of diversity over competence) - but because technology got so much better.

Iven‘s Dad

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Robora Sim: A PyBullet-Powered Environment for Learning Robotic Physical Intelligence We are currently building our Robora simulation environment setup for our sim based learning, leveraging PyBullet, an industry-standard physics engine widely used in AI-driven robotics research and development. The environment is optimized with GPU-accelerated learning algorithms, enabling high-speed imitation learning and reinforcement learning within a safe and controlled virtual setup before shipping out to real world. This simulation platform allows our models to learn, adapt, and generalize across different robot morphologies, terrain types and task objectives - all before deployment to the real world. At it's core, the system combines a VLA-powered high-level planner with low-level motion control algorithms, working cohesively to produce emergent, physically intelligent behaviors. This synergy between simulation, learning, and real-world transfer marks a major step forward in our pursuit of adaptive and intelligent robotic systems. Through advanced domain randomization and synthetic data generation, the Robora Simulation Environment ensures that policies trained in simulation transfer effectively to real-world robots, minimizing the sim-to-real gap. Moreover, users will be able to test and integrate their own hardware kits within selected simulation environments in the Robora Dapp, ensuring seamless compatibility and safer real-world implementation.

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