Legged robot running using a physics-data hybrid motion template
Journal
IEEE Transactions on Robotics
Journal Volume
37
Journal Issue
5
Pages
1680-1695
Date Issued
2021
Author(s)
Abstract
We report on the methodology of developing a hybrid model and utilizing it as a template to initiate running behavior in a legged robot. The hybrid model is comprised of a physics-based, rolling, spring-loaded, inverted pendulum (R-SLIP) model, and a data-driven model that compensates for unmodeled dynamics using Gaussian process (GP) regression. The hybrid R-SLIP-GP model retains the R-SLIP's intrinsic running dynamics, as well as improves the template's accuracy without intensive data training and iteration efforts. The proposed hybrid model was evaluated via simulation and in empirical robot running experiments. The results confirm that the added GP-based model greatly improved the model's accuracy, especially discrepancies resulting from the originally difficult-to-model complex leg-ground interactions. In addition, the R-SLIP-GP model was utilized as a complete motion template to design and control the robot's running motion. The experimental results demonstrate that the hybrid template can initiate more stable and power-efficient running motion in the robot than using the R-SLIP template. ? 2021 IEEE.
Subjects
Gaussian process (GP) regression
Inverted pendulum
Legged robot
Rolling
Running
Spring-loaded
Template
Trajectory optimization
Agricultural robots
Iterative methods
Machine design
Data-driven model
Design and control
Gaussian process
Model complexes
Motion templates
Power efficient
Unmodeled dynamics
Robots
Type
journal article