description

Online control design using a high-fidelity, full-order model for a bipedal robot can be challenging due to the size of the state space of the model. A commonly adopted solution to overcome this challenge is to approximate the full-order model (anchor) with a simplified, reduced-order model (template), while performing control synthesis. Unfortunately it is challenging to make formal guarantees about the safety of an anchor model using a controller designed in an online fashion using a template model. To address this problem, we proposed a method to generate safety-preserving controllers for anchor models by performing reachability analysis on template models while bounding the modeling error. This work describes how this reachable set can be incorporated into a Model Predictive Control framework to select controllers that result in safe walking on the anchor model in an online fashion. The method is illustrated on a 5-link RABBIT model, and is shown to allow the robot to walk safely while utilizing controllers designed in an online fashion.

related Publication

  • J. Liu, P. Zhao, Z. Gan, M. Johnson-Roberson, and R. Vasudevan, "Leveraging the Template and Anchor Framework for Safe, Online Robotic Gait Design," IEEE International Conference on Robotics and Automation, 2020, Accepted. [arXiv]

@article{liu2019leveraging,
  title={Leveraging the Template and Anchor Framework for Safe, Online Robotic Gait Design},
  author={Liu, Jinsun and Zhao, Pengcheng and Gan, Zhenyu and Johnson-Roberson, Matthew and Vasudevan, Ram},
  journal={arXiv preprint arXiv:1909.11125},
  year={2019}
}