quickstart_mujoco-1.1.목표, 계획, reference

목표

Mujoco에서 Task and Motion Planning

Motivation

Study for Task and Motion Planning (for path, not for trajectory) (monte carlo tree search in continuous spaces using Voronoi optimistic optimization with regret bounds - kaist 김범준 교수) url

계획

• Mujoco api, mujoco xml, robosuite(mujoco_py는 deprecated) 사용방법숙지
• Kinematics
• Manipulator (Franka panda, Kuka, UR5e, Sawyer, etc..) 불러오기
• Collision Check
• Joint Position Control
• Cartesian Planning
• RRT* Motion Planning
• Pick and Place 모듈 개발하기
• Task and Motion Planning 데모

향후 필요할 reference

• mujoco colab example https://colab.research.google.com/github/google-deepmind/mujoco/blob/main/python/tutorial.ipynb#scrollTo=slhf39lGxvDI
• robosuite https://robosuite.ai/docs/quickstart.html
• mujoco example (using python wrapper) https://github.com/tayalmanan28/MuJoCo-Tutorial
• mujoco example (c++) https://pab47.github.io/mujoco.html

참고

• mujoco 학습 roadmap 참고 https://ropiens.tistory.com/168
• MJCF 파일 분석(1) - 나만의 Manipulator task를 mujoco에서 만들자 https://rlwithme.tistory.com/8
• mujoco bootcamp https://pab47.github.io/mujoco.html
• MuJoCo 200 Tutorials https://www.youtube.com/playlist?list=PLc7bpbeTIk758Ad3fkSywdxHWpBh9PM0G
• mujoco와 issac gym 시뮬레이터 사이의 Sim2Sim Gap https://www.youtube.com/watch?v=0rgd-fuL-wc
• ropiens (https://ropiens.tistory.com/)
• 미니멀공대생 (https://m.blog.naver.com/PostList.naver?blogId=nswve )
• 오로카 (https://cafe.naver.com/openrt/10561)
• install mujoco to work with openai-gym (https://neptune.ai/blog/installing-mujoco-to-work-with-openai-gym-environments)
• MuJoCo 200 Tutorials https://www.youtube.com/playlist?list=PLc7bpbeTIk758Ad3fkSywdxHWpBh9PM0G
• Mujoco MPC