• Robot Motion: PID Control and Vehicle Models

    Tunnel Tokyo(トンネル東京)

    Hi, * Note that the meetup will be held at Tunnel Tokyo in Osaki Have you ever seen a robot moving so smooth and wondered what kind of technology supports that? This week, we will go through the topic of PID control, diving deep into the algorithms and parameter optimization. Depending on participating members, we can also review and discuss previous topics in Deep Learning, Machine Learning, Neural Networks, Computer Vision, Sensor Fusion, Localization, Control, etc. Please feel free to join us even if you are new to the group or to the field of Autonomous Driving. Space is limited to 8, please RSVP early to secure a spot (please send us a message including your 1) full name and 2) email address so we can provide you the QR code for entering the venue). Once you arrived, please use the QR code we will send you before the event to enter the building. When arrived on the 9th floor, please tell the reception that you are here for meetup from PSYGIG株式会社 and ask them for direction to the "sky blue" meeting room. If you have any questions, feel free to message us. Looking forward to seeing you soon!

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  • Autonomous Drone Talks + TGIF Happy Hours

    Ark Hills

    # Autonomous Drone Talks + Casual TGIF Happy Hours こんにちは! 7月20日(金)18:00よりAutonomous Drone Talks + TGIF Happy Hour Meetupを開催します. Hi all! We will be hosting a couple talks on autonomous drone starting at 6pm. The rest of the evening from 7pm will just be TGIF Happy Hours. Limit to 10 spots. Come join us and catch up over drinks, snacks, and board games! <開催概要/Event Details> 【日 程/Date】 2018年7月20日(金) / Friday, July 20th,[masked]:00 - 20:30 【場 所/Place】〒[masked] 東京都港区赤坂1丁目12-32アーク森ビル3F CrossOver Lounge / Ark Mori Building 3rd Floor CrossOver Lounge,[masked] Akasaka, Minato-ku, Tokyo,[masked] Japan 【参加費/Fee】 無料/Free

  • Udacity Self-Driving Car - Path Planning

    TECH LAB PAAK

    Hi, * Note that the meetup will be held at TECH LAB PAAK in Shibuya instead of Ebisu Please feel free to join us even if you are new to the group or to the field of Autonomous Driving. With the computer vision you have learned and developed, your car/drone/robot should now be able locate itself in a 2D/3D map. The question is, how do you get your car/drone/robot to move from point A to point B in the map? This week, we will go through the topic of Path Planning, diving deep into the algorithms and the implementation in C++. Depending on participating members, we can also review and discuss previous topics in Deep Learning, Machine Learning, Neural Networks, Computer Vision, Sensor Fusion, Localization, Control, etc. We don't usually serve food, but there will be drinks and pizzas sponsored by PSYGIG株式会社 this time. Space is limited to 8, please RSVP early to secure a spot. Once you arrived, you will have to first sign-in at the reception on 6th floor.

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  • Halloween Self-Driving Car Term 2 Review @ Shibuya

    メンバーに表示されるロケーション

    Hi, ***** Note that the meetup will be held in a new office space in Shibuya instead of Ebisu ***** Please feel free to join us even if you are new to the group or to the field of Autonomous Driving. This will be the final week for Term 2 Discussion until Term 3 starts. We will go through the topic of Model Predictive Control and/or any other topics the group would like to review. You will have to first sign-in at the reception on 6th floor, and then find us on 7th floor. If you arrived after 7pm, please send me a message or leave a comment once you arrived 6th floor. Space is limited to 6, please RSVP early to secure a spot. It's also Halloween, expect many scary monsters/creatures/characters on your way to/from Shibuya :D

  • Udacity Self-Driving Car - Localization

    メンバーに表示されるロケーション

    Hi, Please feel free to join us even if you are new to the group or to the field of Autonomous Driving. This week, we will go through the topic of Localization, starting with an overview and then dive deeper into the Markov Localization and/or Particle Filter. Join us in the meeting room of the Open Network Space (https://onlab.jp/space/): 〒[masked], 3 Chome-5 Ebisuminami, Shibuya, Tokyo[masked] https://goo.gl/maps/HdsS8yyTfkF2 The door to the place might be locked. Please send me a message or leave a comment when you arrive at the door please. Space is limited to 8, please RSVP early to secure a spot.

  • International Meetup by ROS Japan UG x Tokyo ROS Meetup x PSYGIG

    メンバーに表示されるロケーション

    ¥1,000

    Hi, We will be co-hosting the International Meetup with ROS Japan User Group, Tokyo ROS Meetup, and PSYGIG. Join us for the latest and hottest topics in robotics! Please visit connpass for more info: https://rosjp.connpass.com/event/66671/ Details(概要) Title(内容):ROS Japan UG #14 International Meetup Date(日時):October 7th, 1:45pm doors open, 2:00pm start(10月7日 13:45開場、14:00開始) Fee(料金):Normal: JPY1000, Students: JPY500 (社会人1000円、学生500円) Location(場所):Digital Garage 9F (https://www.google.co.jp/maps/place/3+Chome-5-7+Ebisuminami,+Shibuya-ku,+T%C5%8Dky%C5%8D-to+150-0022/@35.6462807,139.7016152,17z/data=!4m13!1m7!3m6!1s0x60188b465fc04f0b:0x346d0cf0125cbe89!2s3+Chome-5-7+Ebisuminami,+Shibuya-ku,+T%C5%8Dky%C5%8D-to+150-0022!3b1!8m2!3d35.6462764!4d139.7038039!3m4!1s0x60188b465fc04f0b:0x346d0cf0125cbe89!8m2!3d35.6462764!4d139.7038039?hl=jp) Venue Sponsors(会場提供):Digital Garage (http://www.garage.co.jp/) Co-organizer: ROS Japan UG, PSYGIG (http://psygig.com/), Tokyo ROS Meetup (https://www.meetup.com/Tokyo-ROS-Meetup/) Note that this event is basically in English instead of Japanese. Hope not only Japanese but also non-Japanese to participate in. 本イベントは日本人だけでなく外国人の参加も期待されます。そのため、これまでのイベントと違い、基本的に日本語ではなく英語が使われます。 ご注意ください。 今回の勉強会は、日本人以外の参加が見込まれます。そのため、口頭発表自体は日本語・英語どちらでも構いませんが、少なくとも発表資料は英文で作成する必要があります。 発表希望者は、発表者枠で参加申し込みの上、本イベントページのフィード欄に発表タイトル(英文)をご連絡ください。先着順で対応し、スケジュールに反映させます。 発表終了後、資料公開が可能な方は、本イベントページから資料投稿にご協力お願いします。 Message to Attendees(一般参加者へ) If you plan to tweet or post to somewhere with regards to the event, please use #rosjp. Thank you for your participation. The registration fee is scheduled to buy snack and drink. 今回の勉強会では、英語での発表も予定されていますが、同時通訳のようなことは提供できません。参加者にはある程度の英会話能力が必要です。 ROS, ROS Japan Users Groupに関するツイート、投稿などには、ぜひ #rosjp を付けて発信してください。 参加費はお菓子や飲み物の購入に使われる予定です。

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  • Udacity Self-Driving Car - Lidar and Radar Sensor Fusion 4

    メンバーに表示されるロケーション

    Hi, Please feel free to join us even if you are new to the group or to the field of Autonomous Driving. This week, we would like to finish the last topic of Lidar and Radar Sensor Fusion quickly so we can move on to Localization next. We will continue the topic of Unscented Kalman Filters in C++. Join us in the meeting room of the Open Network Space (https://onlab.jp/space/): 〒[masked], 3 Chome-5 Ebisuminami, Shibuya, Tokyo[masked] https://goo.gl/maps/HdsS8yyTfkF2 The door to the place might be locked. Please send me a message or leave a comment when you arrive at the door please. Space is limited to 8, please RSVP early to secure a spot.

  • Self-Driving Car Projects Mini-Hackathon

    メンバーに表示されるロケーション

    Hi, We will be working on Udacity's Self-Driving Car projects this whole day. For the first 2 hours starting at 1pm, we will go through some lectures on Unscented Kalman Filters, Localization, and Deep Learning. Afterwards, we will be mostly working on Extended/Unscented Kalman Filters and Deep Learning for the Behavior Cloning project. Please feel free to join us anytime in the afternoon. This will be a great opportunity to get started on the actual implementation of Sensor Fusion and Deep Learning with other members. Remember to bring your own laptop and get ready to hack! We have some hardware (e.g. NVIDIA Jetson TX2, Movidius Neural Compute Stick with Myriad 2 VPU, LIDAR, etc) that would be useful in testing your code for real world applications. ## Preparation ## 1. Udacity Term 1 Starter Kit: https://github.com/udacity/CarND-Term1-Starter-Kit For those working on Deep Learning in Python, follow the instructions in the Starter Kit to setup Anaconda/Docker, OpenCV, and Tensorflow. 2. Read through the requirements for your project of choice: A. Deep Learning https://github.com/udacity/CarND-Behavioral-Cloning-P3 B. Extended Kalman Filter https://github.com/udacity/CarND-Extended-Kalman-Filter-Project C. Unscented Kalman Filter https://github.com/udacity/CarND-Unscented-Kalman-Filter-Project 3. Additional Resources: Kalman Filters: https://www.udacity.com/course/artificial-intelligence-for-robotics--cs373 ## Location ## Join us at the co-working space in Ebisu called Open Network Space: https://onlab.jp/space/ 〒[masked], 3 Chome-5 Ebisuminami, Shibuya, Tokyo[masked] https://goo.gl/maps/HdsS8yyTfkF2 The door to the place might be locked. Please send me a message or leave a comment when you arrive at the door please. Space is limited to 8, please RSVP early to secure a spot.

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  • Udacity Self-Driving Car - Lidar and Radar Sensor Fusion 3

    メンバーに表示されるロケーション

    Hi, Our venue is not available this week. Our next meetup will be the Thursday a week after. Please feel free to join us even if you are new to the group or to the field of Autonomous Driving. This week, we will go through the topic of Lidar and Radar Sensor Fusion with Unscented Kalman Filters in C++. Join us in the meeting room of the Open Network Space (https://onlab.jp/space/): 〒[masked], 3 Chome-5 Ebisuminami, Shibuya, Tokyo[masked] https://goo.gl/maps/HdsS8yyTfkF2 The door to the place might be locked. Please send me a message or leave a comment when you arrive at the door please. Space is limited to 8, please RSVP early to secure a spot.

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  • Udacity Self-Driving Car - Lidar and Radar Sensor Fusion 2

    メンバーに表示されるロケーション

    Please feel free to join us even if you are new to the group or to the field of Autonomous Driving. This week, we will go through the topic of Lidar and Radar Sensor Fusion with Kalman Filters in C++. Join us in the meeting room of the Open Network Space (https://onlab.jp/space/): 〒[masked], 3 Chome-5 Ebisuminami, Shibuya, Tokyo[masked] https://goo.gl/maps/HdsS8yyTfkF2 The door to the place might be locked. Please send me a message or leave a comment when you arrive at the door please. Space is limited to 8, please RSVP early to secure a spot.

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