Reinforcement Learning of 3D Musculoskeletal Model for Walking or Running with Minimum Efforts

Authors

  •   Vikram Singh Chandel Data Science Student, Manipal University, B-80 Aakriti Gardens, Nehru Nagar, Bhopal - 462 003
  •   Subhabaha Pal Senior Faculty, Data Science and Machine Learning, with Manipal ProLearn (Manipal Academy of Higher Education – South Bangalore Campus), 3rd Floor, Salarpuria Symphony, 7, Service Road, Pragathi Nagar, Electronics City Post, Bengaluru – 560 100

DOI:

https://doi.org/10.17010/ijcs/2020/v5/i2-3/152870

Keywords:

3D Musculoskeletal Model

, Artificial Intelligence, Reinforcement Learning.

Manuscript Received

, April 3, 2020, Revised, April 25, Accepted, May 2, 2020.

Abstract

In this work we are trying to build a controller for a musculoskeletal model that has the goal of matching a given time-varying velocity vector. The major objective is building a musculoskeletal model which is fully comprehensive and reproduces realistic human movements driven by muscle contraction dynamics. Spectrum of human movement will be generated through variations in the anatomic model.

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Published

2020-06-30

How to Cite

Chandel, V. S., & Pal, S. (2020). Reinforcement Learning of 3D Musculoskeletal Model for Walking or Running with Minimum Efforts. Indian Journal of Computer Science, 5(2&3), 36–46. https://doi.org/10.17010/ijcs/2020/v5/i2-3/152870

Issue

Volume 5, Issue 2-3, March-June 2020

Section

Articles
Crossref
Scopus
Google Scholar
Europe PMC

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