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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)

Far3D: Expanding the Horizon for Surround-View 3D Object Detection (AAAI2024)
Far3D: Expanding the Horizon for Surround-View 3D Object Detection (AAAI2024) Summary https://github.com/megvii-research/Far3D multi-camera 3D detection for far detection Method 遠距離はCamera onlyの方が精度良い frustumにfeatureを散布する 全体アーキテクチャ Experiment
2024/12/22 · Surveys
RegTTA3D: Better Regression Makes Better Test-time Adaptive 3D Object Detection (ECCV2024)
RegTTA3D: Better Regression Makes Better Test-time Adaptive 3D Object Detection (ECCV2024) Summary Test-time adaptationを用いた3D detection Domain adaptation Regressionを中心に少ないparameterでtuningできる Method Domain
2024/11/14 · Surveys
デフォルトパラメータとどう付き合うか
デフォルトパラメータとどう付き合うか 概要 ロボットや機械学習では大量のパラメータを扱うことになる Architect（アーキテクチャを考える人）
2024/11/04 · Blogs
CAT-SAM: Conditional Tuning for Few-Shot Adaptation of Segment Anything Model (ECCV2024)
CAT-SAM: Conditional Tuning for Few-Shot Adaptation of Segment Anything Model (ECCV2024) Summary https://xiaoaoran.github.io/projects/CAT-SAM https://github.com/weihao1115/cat-sam “a ConditionAl Tuning network” for SAM SAMに additional pipelineを追加して、元のSAMはfrozenしてadaptationする研究 Method architecture a
2024/11/01 · Surveys
Detecting As Labeling: Rethinking LiDAR-camera Fusion in 3D Object Detection (ECCV2024)
Detecting As Labeling: Rethinking LiDAR-camera Fusion in 3D Object Detection (ECCV2024) Summary from Phigent Robotics CTOが Baidu -> Horizon Robotics の経歴 https://github.com/HuangJunJie2017/BEVDet Camera LiDAR 3D detection において、Camera pipelineはlabel推定にしか使わないようにした
2024/10/27 · Surveys
On-the-fly Category Discovery for LiDAR Semantic Segmentation (ECCV2024)
On-the-fly Category Discovery for LiDAR Semantic Segmentation (ECCV2024) Summary Unknown objectのための LiDAR Semantic Segmentationに必要なカテゴライズの導入 Method Baseは “On-the-fly Category Discovery (CVPR 2023)” https://github.com/PRIS-CV/On-the-fly-Category-Discovery 解きたいタスクの違い (a)
2024/10/27 · Surveys
Towards Stable 3D Object Detection (ECCV2024)
Towards Stable 3D Object Detection (ECCV2024) Summary https://github.com/jbwang1997/StabilityIndex from Nankai University + KargoBot Inc. （自動運転企業） 3D detectionにおける時系列の安定性を考慮したMetrics、Stability Index (SI) の提案
2024/10/27 · Surveys
UniTraj: A Unified Framework for Scalable Vehicle Trajectory Prediction (ECCV2024)
UniTraj: A Unified Framework for Scalable Vehicle Trajectory Prediction (ECCV2024) Summary https://vita-epfl.github.io/UniTraj/ https://github.com/vita-epfl/UniTraj prediction taskを統一的に扱えるフレームワークの提案 巨大なデータでpredictionを学習したら、結局データの大きさが
2024/10/27 · Surveys
モニターにunknown monitorが検出されてsuspendからの復帰でモニターの接続が壊れる問題
モニターにunknown monitorが検出されてsuspendからの復帰でモニターの接続が壊れる問題 概要 モニターにunknown monit
2024/09/21 · Blogs
Rust製可視化ツールのrerunを使ってmmdetection3dの可視化をしてみる
Rust製可視化ツールのrerunを使ってmmdetection3dの可視化をしてみる 概要 Rust製可視化ツールのrerunを使って、mmd
2024/08/17 · Blogs