Utkarsh Agrawal

中文参考

所以我让Jev完全控制猎鹰9级火箭 全面发射到着陆 代码中没有自动驾驶仪，没有脚本轨迹，没有安全否决权 每个决定都是由jev做出的（您可以在视频底部看到决定） 是的，它能够着陆助推器 而所有这一切只需要245个调用和0.04美元的API调用 对于SIM卡，我使用Mujoco 这些布局是42米助推器、425吨重、9台发动机、真实大气层、马赫数相关阻力、风和推进剂消耗 车辆每0.8秒就会崩溃一次，jev的判决发生在~1Hz的频率下，输出时间为~0.4秒 所以我给了jev这些控制 >启动或持有 >每次燃烧的发动机计数（它选择了5个单独着陆！） >何时点燃燃烧 >上升截止、滑行、进入、腿部、达阵 因此，在将所有这些控制交给jev后，实验开始了 经过12次跑动并调整多个东西后，它成功地自行着陆 我会写一篇关于它的完整文章 我做了什么实验， 但最后我想 人们说它只是一个分类器 是的，但它是一个非常好且有效的分类器，其速度和决策为现实生活中的任务和实施开辟了全新的工作 在清理了代码中的混乱之后，我还将为此开源整个仓库 这是简短的演示 I hope you like it

原帖全文 / EN

so I gave jev full control of the falcon-9 class rocket full launch to landing no autopilot, no scripted trajectories, no safety veto in the code every decision was made by jev ( you can see decisions at the bottom of the video) and yeah it was able to land the booster and all this with just 245 calls and and $0.04 in API calls for sim I used mujoco and the configurations were 42m booster, 425 tonnes, 9 engines, real atmosphere, mach dependent drag, wind and propellent depletion the vehicle was going ubstable every .8 secs, and jev's decesion making takes place at ~1Hz and output in ~0.4 sec so I gave jev these controls > launch or hold >engine count for every burn( it chose 5 for landing by itself !) > when to light that burn >ascent cutoff, coast, entry, legs, touchdown so after giving all these controls to jev the experiments begun and after 12 runs and tweaking multiple things it managed to land by itself I will write a full article about it and what I did with experiments and whet I tweaks I made but for some final thoughts people are saying it's just a classifier yes, but it's a very good and effective classifier, and its speed and decision making, open up a whole new work for real life tasks and implementationa I will also open source the whole repo for this after cleaning up the clutter in my code so this is the short demo I hope you like it