Timezone: »

OstrichRL: A Musculoskeletal Ostrich Simulation to Study Bio-mechanical Locomotion
Vittorio La Barbera · Fabio Pardo · Yuval Tassa · Petar Kormushev · John Hutchinson
Event URL: https://openreview.net/forum?id=7KzszSyQP0D »

Muscle-actuated control is a research topic of interest spanning different fields, in particular biomechanics, robotics and graphics. This type of control is particularly challenging because models are often overactuated, and dynamics are delayed and non-linear. It is however a very well tested and tuned actuation model that has undergone millions of years of evolution and that involves interesting properties exploiting passive forces of muscle-tendon units and efficient energy storage and release. To facilitate research on muscle-actuated simulation, we release a 3D musculoskeletal simulation of an ostrich based on the MuJoCo simulator. Ostriches are one of the fastest bipeds on earth and are therefore an excellent model for studying muscle-actuated bipedal locomotion. The model is based on CT scans and dissections used to gather actual muscle data such as insertion sites, lengths and pennation angles. Along with this model, we also provide a set of reinforcement learning tasks, including reference motion tracking and a reaching task with the neck. The reference motion data are based on motion capture clips of various behaviors which we pre-processed and adapted to our model. This paper describes how the model was built and iteratively improved using the tasks. We evaluate the accuracy of the muscle actuation patterns by comparing them to experimentally collected electromyographic data from locomoting birds. We believe that this work can be a useful bridge between the biomechanics, reinforcement learning, graphics and robotics communities, by providing a fast and easy to use simulation.

Author Information

Vittorio La Barbera (Royal Veterinary College)
Fabio Pardo (Imperial College London)
Yuval Tassa (Google DeepMind)
Petar Kormushev
John Hutchinson

More from the Same Authors

  • 2022 : Fifteen-minute Competition Overview Video »
    Guillaume Durandau · Yuval Tassa · Vittorio Caggiano · Vikash Kumar · Seungmoon Song · Massimo Sartori ·
  • 2022 Competition: MyoChallenge: Learning contact-rich manipulation using a musculoskeletal hand »
    Vittorio Caggiano · · Guillaume Durandau · Seungmoon Song · Yuval Tassa · Massimo Sartori · Vikash Kumar
  • 2018 : Poster Session 1 + Coffee »
    Tom Van de Wiele · Rui Zhao · J. Fernando Hernandez-Garcia · Fabio Pardo · Xian Yeow Lee · Xiaolin Andy Li · Marcin Andrychowicz · Jie Tang · Suraj Nair · Juhyeon Lee · C├ędric Colas · S. M. Ali Eslami · Yen-Chen Wu · Stephen McAleer · Ryan Julian · Yang Xue · Matthia Sabatelli · Pranav Shyam · Alexandros Kalousis · Giovanni Montana · Emanuele Pesce · Felix Leibfried · Zhanpeng He · Chunxiao Liu · Yanjun Li · Yoshihide Sawada · Alexander Pashevich · Tejas Kulkarni · Keiran Paster · Luca Rigazio · Quan Vuong · Hyunggon Park · Minhae Kwon · Rivindu Weerasekera · Shamane Siriwardhanaa · Rui Wang · Ozsel Kilinc · Keith Ross · Yizhou Wang · Simon Schmitt · Thomas Anthony · Evan Cater · Forest Agostinelli · Tegg Sung · Shirou Maruyama · Alexander Shmakov · Devin Schwab · Mohammad Firouzi · Glen Berseth · Denis Osipychev · Jesse Farebrother · Jianlan Luo · William Agnew · Peter Vrancx · Jonathan Heek · Catalin Ionescu · Haiyan Yin · Megumi Miyashita · Nathan Jay · Noga H. Rotman · Sam Leroux · Shaileshh Bojja Venkatakrishnan · Henri Schmidt · Jack Terwilliger · Ishan Durugkar · Jonathan Sauder · David Kas · Arash Tavakoli · Alain-Sam Cohen · Philip Bontrager · Adam Lerer · Thomas Paine · Ahmed Khalifa · Ruben Rodriguez · Avi Singh · Yiming Zhang
  • 2016 Poster: Attend, Infer, Repeat: Fast Scene Understanding with Generative Models »
    S. M. Ali Eslami · Nicolas Heess · Theophane Weber · Yuval Tassa · David Szepesvari · koray kavukcuoglu · Geoffrey E Hinton
  • 2015 Poster: Learning Continuous Control Policies by Stochastic Value Gradients »
    Nicolas Heess · Gregory Wayne · David Silver · Timothy Lillicrap · Tom Erez · Yuval Tassa