Lifting Task Stability Evaluation Based on Balanced State Basins of a Humanoid Robot

Abstract

Abstract Stability evaluation is a vital aspect of successful balance control and design for humanoid robots. While balance stability has been extensively explored for push recovery during legged locomotion tasks in response to perturbations, less effort has been devoted toward developing a similar understanding for lifting tasks. Lifting involves unique interactions between the robot and lifted object, whose mass can significantly alter the mass distribution of the loaded robot and the upper extremities, which are typically ignored in legged robot balance. In this study, the balance stability of a humanoid robot during a lifting task is evaluated with a partition-based approach in the augmented center-of-mass-state space. The balanced state boundary is computed through an optimization-based method that incorporates the loaded robot’s whole-body system properties, such as kinematic and actuation limits, with full-order nonlinear system dynamics in the sagittal plane subject to foot-ground contact interactions and lifting task requirements. The boundaries are constructed for different combinations of object masses and lifting trajectories obtained with a zero-moment point constraint-based pattern generator. Trends in the boundaries and comparisons among them are used to identify the effect of different loading conditions and task parameters on balance stability due to kinematic and actuation limits, linear and angular momenta regulation, and mass distribution.