Scepter914 Website

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Biography

Profile

  • Name: Satoshi Tanaka

Work Experience

  • Aug. 2025 - Freelance engineer
  • Apr. 2020 - Jul. 2025, TIER IV, Inc.
    • Jun. 2024 - Jul. 2025 Lead Software Engineer for MLOps in perception module
    • Apr. 2020 - Dec. 2023 Software Engineer for Autonomous Driving
  • Internship
    • Apr. 2018 - Apr. 2019, Internship at Preferred Networks, Inc. as a part-time engineer
    • Aug. 2017 - Mar. 2018, Internship at Hitachi, Ltd as a research assistant

Academic Background

  • Master’s Degree in Information Science and Engineering, the University of Tokyo
    • Apr. 2018 - Mar. 2020, Ishikawa Senoo Lab, Department of Creative Informatics, Graduate School of Information Science and Technology
  • Bachelor’s Degree in Precision Engineering, the University of Tokyo
    • Apr. 2017 - Mar. 2018, Kotani Lab, Research Center for Advanced Sceience and Technology
    • Apr. 2016 - Mar. 2018, Dept. of Precison Engineering
    • Apr. 2014 - Mar. 2016, Faculty of Liberal Arts

Interest

  • Robotics, Computer Vision, Control Theory
  • Building autonomous robotic systems that can interact with the physical world faster and more dexterously than humans
    • Real-time 3D object detection
    • Development of mechanisms capable of fast and compliant motion
    • Force control for dynamic manipulation

Publication

International Conference (First author)

  • Satoshi Tanaka, Keisuke Koyama, Taku Senoo, Makoto Shimojo, and Masatoshi Ishikawa, High-speed Hitting Grasping with Magripper, a Highly Backdrivable Gripper using Magnetic Gear and Plastic Deformation Control, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2020), Proceedings, pp. 9137 - 9143. [2020 IEEE Robotics and Automation Society Japan Joint Chapter Young Award]
  • Satoshi Tanaka, Keisuke Koyama, Taku Senoo, and Masatoshi Ishikawa, Adaptive Visual Shock Absorber with Visual-based Maxwell Model Using Magnetic Gear, The 2020 International Conference on Robotics and Automation (ICRA2020), Proceedings, pp. 6163-6168.
  • Satoshi Tanaka, Taku Senoo, and Masatoshi Ishikawa, Non-Stop Handover of Parcel to Airborne UAV Based on High-Speed Visual Object Tracking, 2019 19th International Conference on Advanced Robotics (ICAR2019), Proceedings, pp. 414-419.
  • Satoshi Tanaka, Taku Senoo, and Masatoshi Ishikawa, High-speed UAV Delivery System with Non-Stop Parcel Handover Using High-speed Visual Control, 2019 IEEE Intelligent Transportation Systems Conference (ITSC19), Proceedings, pp. 4449-4455.

ArXiv papers (First author)

  • Satoshi Tanaka, Koji Minoda, Fumiya Watanabe, Takamasa Horibe, Rethink 3D Object Detection from Physical World, arXiv 2025, https://arxiv.org/abs/2507.00190.
  • Satoshi Tanaka, Samrat Thapa, Kok Seang Tan, Amadeusz Szymko, Lobos Kenzo, Koji Minoda, Shintaro Tomie, Kotaro Uetake, Guolong Zhang, Isamu Yamashita, Takamasa Horibe, AWML: An Open-Source ML-based Robotics Perception Framework to Deploy for ROS-based Autonomous Driving Software, arXiv 2025, https://arxiv.org/abs/2506.00645.

International Conference (Not first author)

  • Taisei Fujimoto, Satoshi Tanaka, and Shinpei Kato, LaneFusion: 3D Object Detection with Rasterized Lane Map, the 2022 33rd IEEE Intelligent Vehicles Symposium (IV 2022), Proceedings, pp. 396-403.

Other publication

  • Kazunari Kawabata, Manato Hirabayashi, David Wong, Satoshi Tanaka, Akihito Ohsato AD perception and applications using automotive HDR cameras, the 4th Autoware workshop at the 2022 33rd IEEE Intelligent Vehicles Symposium (IV 2022)

Award, Scholarship

Projects

(Research) Rethink 3D Object Detection from Physical World

AWML

DepthAnything-ROS



(Research) High-speed Hitting Grasping with Magripper

  • Developed high-speed hitting grasping executed seamlessly from reaching with Magripper, a highly backdrivable gripper, and hitting grasping, high-speed grasping framework.
  • Accepted at IROS2020 [2020 IEEE Robotics and Automation Society Japan Joint Chapter Young Award]

(Research) Adaptive Visual Shock Absorber with Magslider

  • Developed visual shock absorber system with high-speed vision, high-backdrivablilty hardware, and force control.
  • Accepted at ICRA2020

(Research) High-speed supply station for UAV delivery system

  • Developed high-speed supply station for UAV delivery system
  • Accepted at ITSC2019


Robotic Competition

  • Team Leader for ABU Robocon2016
  • Winner of National Championships, 2nd-runnerup of ABU Robocon, ABU Robocon award.
  • Visited to the prime minister’s residence as the team leader of representation from Japan team. Reported by link and link.

Other projects

Latest change (blog, survey)

Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks (ICRA2019)
Summary Raster mapを用いた1 agent multi-modal prediction https://github.com/nutonomy/nuscenes-devkit/blob/master/python-sdk/nuscenes/prediction/models/mtp.py github code 確率とともに複数経路(= multi-modal) を出力できるように拡張 single modalだと行きもしないところのpathが出てくる Method i: a
2021/10/10 · Surveys
Multiple Trajectory Prediction with Deep Temporal and Spatial Convolutional Neural Networks (IROS2020)
summary temporal convolutional networks (TCNs) を用いたPredictionの提案 Method 軽くて良さげな全体framework mobilenetなのがrealtimeを考慮していて良い
2021/10/10 · Surveys
MVLidarNet: Real-Time Multi-Class Scene Understanding for Autonomous Driving Using Multiple Views (IROS2020)
Summary Link https://arxiv.org/abs/2006.05518 arxiv版 https://www.youtube.com/watch?v=2ck5_sToayc https://www.youtube.com/watch?v=T7w-ZCVVUgM https://blogs.nvidia.com/blog/2020/03/11/drive-labs-multi-view-lidarnet-self-driving-cars/ nvidia blog githubはない 2020/10現在 Two-stage型 Lidar 3d multi-class detection framework “multi-view” = “perspecti
2021/10/10 · Surveys
One Million Scenes for Autonomous Driving: ONCE Dataset (2021/06 arxiv)
summary ONCE (One millioN sCenEs) dataset Huaweiから出たDataset baselibeについて色々結果をまとめているのでsurvey記事として価値が高い baseli
2021/10/10 · Surveys
Optimising the selection of samples for robust lidar camera calibration (arxiv 2021/03)
Summary 使いやすい形になっているっぽい https://gitlab.acfr.usyd.edu.au/its/cam_lidar_calibration https://www.youtube.com/watch?v=WmzEnjmffQU 素人でもcalibrationができるようなtarget-based なLidar- Camera calibのパイプラ
2021/10/10 · Surveys
The Importance of Prior Knowledge in Precise Multimodal Prediction (IROS2020)
summary UberによるPrediction framework REINFORCE の提案 Mapや交通ルールから好ましい予測のoutputを出したいが、基本的に微分不可能 REINFORCE gradient estim
2021/10/10 · Surveys
Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving (arxiv2018, WACV2020)
Summary from Uber 1 agentごとの静的地図+他の車両など動的状況をラスタライズ化した画像をinputとした1 agent, single-modal prediction Background Method Input Rasterized input RGBの3chのデータ 道路
2021/10/10 · Surveys
画像・動画・カメラ入力を扱うインターフェイスのライブラリをRustで作って公開した
画像・動画・カメラ入力を扱うインターフェイスのライブラリをRustで作って公開した 概要 動画像処理において、カメラinput・mp4動画・1枚
2021/09/05 · Blogs
使ってて良かった家電・ガジェット類の紹介
使ってて良かった家電・ガジェット類の紹介 概要 使ってて良かった家電・ガジェット類の紹介 同僚に「買ってよかったランキングを聞かせてくれ」と聞かれ
2021/09/03 · Blogs
Rustでの画像保存の高速化
Rustでの画像保存の高速化 概要 image crateのpngのsaveがなんか時間かかるのをppmで高速に保存する https://github.com/scepter914/camera-image-processing-template 実装とかはここに置いた 実装 ちまち
2021/08/22 · Blogs