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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
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Posts
How to install frankx
Published:
How to install frankx to Ubuntu18
tf2rl
Published:
tf2rl: TensorFlow2 Reinforcement Learning
OpenCV-Python tips
Published:
OpenCV-Python Tips
MuJoCo install tips
Published:
MuJoCo installに関するTips
zshでextra_requireのパッケージをインストールする
Published:
zshではpip install -e .[hoge]が失敗するのでその対策をする
Safety Gym
Published:
SafetyGymが公開されたので試してみた
WindowsでC++17をCythonでビルドしてPythonから使うために
Published:
C++17をMinGW+GCCを使ってビルドする
portfolio
模擬人工衛星 CanSat
ARLISS2013（優勝）、ARLISS2014、ARLISS2015
チャーハンロボットの設計・製作・制御
第17回ロボットグランプリ 優勝
4軸ロボットアームの設計・製作・制御を担当
衛星設計コンテスト
2014年アイデア大賞：五輪紋章創造衛星武蔵
2015年設計大賞：重力波天体観測衛星ひばり
地球・天体観測衛星TSUBAME
C&DH系組込SW開発，衛星自動運用システム，プロジェクトマネージャを担当
自作スピーカ
フルレンジスピーカの製作
DLAS: Deep Learning Attitude Sensor
オンボード衛星画像分類ソフトウェア開発，プロジェクトマネージャを担当
publications
Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning
Published in IROS, 2019
This paper proposes a RL-based algorithm for trajectory optimization for constrained dynamical systems.
Download here
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?
Published in ICML, 2020
This paper intentionally increases input dimensionality to improve the performance of Deep RL algorithms. The proposed OFENet significantly improves sample efficiency and final performance of RL algorithms.
Download here
Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path
Published in IROS, 2020
This paper proposes to decouple planning and control by combining traditional path planning algorithms, supervised learning (SL) and reinforcement learning (RL) algorithms in a synergistic way. By exploiting waypoints produced from SL, an RL agent easily learns to navigate to arbitrary goal locations, and generalize to novel environments.
Download here
Deep Reactive Planning in Dynamic Environments
Published in CoRL, 2020
This paper proposes a reactive planning in dynamic environments.
Download here
talks
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.