aiki

Asahigaoka71st→Dept. of Mechanical System Engineering, Graduate School of Nagoya Univ. D1 /Robotics and Planning

[aiki @aiki253]

@mtakuma32 😭

[aiki @aiki253]

#自動制御連合講演会
#rengo68
#MAGP
#自動運転
#ミニカー
#名古屋大学

[aiki @aiki253]

本日より2日間名古屋大学で開催の自動制御連合講演会の併催行事として、自動運転ミニカー大会’MAGP’が第二体育館(剣道場)にてやっています。学会参加者の方も一般の方も無料で見学できますので是非お越しください
特に明日11月2日は人間vsAIのミニカー対決もあります✨
↓詳細
https://t.co/FQ0tLTfahi

[Shigemichi Matsuzaki @S_Matsuzaki94]

12月2日、『ロボット自律移動の理論と実践』と題したセミナーを開催いたします！
計画から制御、モデルベースから学習ベース、理論からアプリまで幅広いトピックをお話しいただきます。
完全に個人の趣味です。
めっちゃ楽しみ！！！！！！！
https://t.co/M0le119U1d

[aiki @aiki253]

@tokagemodoki_nu 😭
おつかれさま、ご飯行こう！

[aiki @aiki253]

博士後期課程へ進学します。
3年間JST BOOSTの支援の下、歩行者共存環境での移動ロボットのナビゲーションにブレイクスルーを起こせるような成果を創出できるように頑張ります。

[aiki @aiki253]

僕も出場してます、明日の10:30から僕たちのチームの予選タイムアタックがあるので、名古屋近辺にいる方は是非見に来てください！名古屋大学の剣道場(第3体育館)でやってます
決勝トーナメントは午後2時からです！

[MAGP-Minicar Autonomous Grand Prix- @F1TenthJAPAN]


🏎️明日はMAGP第1回大会の決勝戦！🏁

自動運転ミニカーが名古屋大学の特設コースを駆け抜ける迫力の走行映像をお届け
 機械学習から制御技術まで、エンジニアの技術と情熱が詰まった熱いバトル！
見学無料✨ぜひ会場(名古屋大学・剣道場)にお越しください！

#MAGP #自動運転 #ミニカー #Roboracer

[Naoki Akai（赤井直紀） @naokiakai]

ROS 2で動くLIO＋LiDAR SLAM＋Localizationを1パッケージにまとめた『plain_slam_ros2』を公開しました。
オーソドックスな技術で構成し、C++コアは1800行未満のミニマル設計で、可読性もかなり重視しました。
SLAM実装の参考になれば幸いです。
https://t.co/qGgMidlfEx

[aiki @aiki253]

@uv_bon おめでとー！！

[aiki @aiki253]

@love_love_it @NU_kaban @Qualis_7 ゴールデンウィークですもんね、一旦LINEにしましょか

[aiki @aiki253]

@Qualis_7 @NU_kaban @love_love_it 夜ご飯食べれる感じなんです？
やっさんは何時から何時まで会えるの？

[aiki @aiki253]

@Qualis_7 名古屋帰ってきますか？

[aiki @aiki253]

@mnnnmnnnnnmn 就活の写真は顔赤くなくて安心したわ笑

[aiki @aiki253]

@44444444xxxx1 おめでとう！！

と同時に満点が変わってて？びっくりしました

[Mizuho Aoki @mizuhoaoki1998]

Here is a GPU-enabled docker environment for easily starting Genesis, a universal physics engine.
https://t.co/whW9TM3N5W

[aiki @aiki253]

これすごすぎる…年末年始時間に余裕できたらこれで遊びたい…

[Zhou Xian @zhou_xian_]

Everything you love about generative models — now powered by real physics!

Announcing the Genesis project — after a 24-month large-scale research collaboration involving over 20 research labs — a generative physics engine able to generate 4D dynamical worlds powered by a physics simulation platform designed for general-purpose robotics and physical AI applications.

Genesis's physics engine is developed in pure Python, while being 10-80x faster than existing GPU-accelerated stacks like Isaac Gym and MJX. It delivers a simulation speed ~430,000 faster than in real-time, and takes only 26 seconds to train a robotic locomotion policy transferrable to the real world on a single RTX4090 (see tutorial: https://t.co/bEkIlCKqdf).

The Genesis physics engine and simulation platform is fully open source at https://t.co/DhBv7NdyqH. We'll gradually roll out access to our generative framework in the near future.

Genesis implements a unified simulation framework all from scratch, integrating a wide spectrum of state-of-the-art physics solvers, allowing simulation of the whole physical world in a virtual realm with the highest realism.

We aim to build a universal data engine that leverages an upper-level generative framework to autonomously create physical worlds, together with various modes of data, including environments, camera motions, robotic task proposals, reward functions, robot policies, character motions, fully interactive 3D scenes, open-world articulated assets, and more, aiming towards fully automated data generation for robotics, physical AI and other applications.

Open Source Code: https://t.co/DhBv7NdyqH
Project webpage: https://t.co/SBNyhFB0yn

Documentation: https://t.co/3yuBoaealV

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[Zhou Xian @zhou_xian_]

Everything you love about generative models — now powered by real physics!

Announcing the Genesis project — after a 24-month large-scale research collaboration involving over 20 research labs — a generative physics engine able to generate 4D dynamical worlds powered by a physics simulation platform designed for general-purpose robotics and physical AI applications.

Genesis's physics engine is developed in pure Python, while being 10-80x faster than existing GPU-accelerated stacks like Isaac Gym and MJX. It delivers a simulation speed ~430,000 faster than in real-time, and takes only 26 seconds to train a robotic locomotion policy transferrable to the real world on a single RTX4090 (see tutorial: https://t.co/bEkIlCKqdf).

The Genesis physics engine and simulation platform is fully open source at https://t.co/DhBv7NdyqH. We'll gradually roll out access to our generative framework in the near future.

Genesis implements a unified simulation framework all from scratch, integrating a wide spectrum of state-of-the-art physics solvers, allowing simulation of the whole physical world in a virtual realm with the highest realism.

We aim to build a universal data engine that leverages an upper-level generative framework to autonomously create physical worlds, together with various modes of data, including environments, camera motions, robotic task proposals, reward functions, robot policies, character motions, fully interactive 3D scenes, open-world articulated assets, and more, aiming towards fully automated data generation for robotics, physical AI and other applications.

Open Source Code: https://t.co/DhBv7NdyqH
Project webpage: https://t.co/SBNyhFB0yn

Documentation: https://t.co/3yuBoaealV

1/n