Posture Control—Human-Inspired Approaches for Humanoid Robot Benchmarking: Conceptualizing Tests, Protocols and Analyses

摘要

Posture control is indispensable for both humans and humanoid robots, which becomes especially evident when performing sensorimotor tasks such as moving on compliant terrain or interacting with the environment. Posture control is therefore targeted in recent proposals of robot benchmarking in order to advance their development. This article suggests corresponding robot tests of standing balance, drawing inspirations from the human sensorimotor system and presenting examples from robot experiments. To account for a considerable technical and algorithmic diversity among robots, we focus in our tests on basic posture control mechanisms, which provide humans with an impressive postural versatility and robustness. Specifically, we focus on the mechanically challenging balancing of the whole body above the feet in the sagittal plane around the ankle joints in concert with the upper body balancing around the hip joints. The suggested tests target three key issues of human balancing, which appear equally relevant for humanoid bipeds: (1) Four basic physical disturbances (support surface tilt and translation, field and contact forces) may affect the balancing in any given degree of freedom (DoF). Targeting these disturbances allows us to abstract from the manifold of possible behavioral tasks. (2) Posture control interacts in a conflict-free way with the control of voluntary movements for undisturbed movement execution, both with ‘reactive’ balancing of external disturbances and ‘proactive’ balancing of self-produced disturbances from the voluntary movements. Our proposals therefore target both types of disturbances and their superposition. (3) Relevant for both versatility and robustness of the control, linkages between the posture control mechanisms across DoFs provide their functional cooperation and coordination at will and on functional demands. The suggested tests therefore include ankle-hip coordination. Suggested benchmarking criteria build on the evoked sway magnitude, normalized to robot weight and COM height, in relation to reference ranges that remain to be established. The references may include human likeness features. The proposed benchmarking concept may in principle also be applied to wearable robots, where a human user may command movements, but may not be aware of the additionally required postural control, which then needs to be implemented into the robot.