Trunk Pitch Oscillations for Joint Load Redistribution in Humans and Humanoid Robots

TL;DR

This paper investigates how trunk oscillations, inspired by human running, can be modeled and used to redistribute joint loads and improve energy efficiency in humanoid robots.

Contribution

It introduces a novel trunk oscillation model using a TSLIP with a virtual point, linking human trunk motion patterns to robotic gait control.

Findings

Positioning the virtual point below the CoM induces forward trunk pitching.

Trunk oscillations reduce leg load through hip-leg work synergy.

Trade-off observed between load reduction and increased hip torque.

Abstract

Creating natural-looking running gaits for humanoid robots is a complex task due to the underactuated degree of freedom in the trunk, which makes the motion planning and control difficult. The research on trunk movements in human locomotion is insufficient, and no formalism is known to transfer human motion patterns onto robots. Related work mostly focuses on the lower extremities, and simplifies the problem by stabilizing the trunk at a fixed angle. In contrast, humans display significant trunk motions that follow the natural dynamics of the gait. In this work, we use a spring-loaded inverted pendulum model with a trunk (TSLIP) together with a virtual point (VP) target to create trunk oscillations and investigate the impact of these movements. We analyze how the VP location and forward speed determine the direction and magnitude of the trunk oscillations. We show that positioning the VP below the center of mass (CoM) can explain the forward trunk pitching observed in human running. The VP below the CoM leads to a synergistic work between the hip and leg, reducing the leg loading. However, it comes at the cost of increased peak hip torque. Our results provide insights for leveraging the trunk motion to redistribute joint loads and potentially improve the energy efficiency in humanoid robots.