Passive and dynamic gait measures for biped mechanism: formulation and simulation analysis

Abstract

Understanding and mimicking human gait is essential for design and control of biped walking robots. The unique characteristics of normal human gait are described as passive dynamic walking, whereas general human gait is neither completely passive nor always dynamic. To study various walking motions, it is important to quantify the different levels of passivity and dynamicity, which have not been addressed in the current literature. In this paper, we introduce the initial formulations of Passive Gait Measure (PGM) and Dynamic Gait Measure (DGM) that quantify passivity and dynamicity, respectively, of a given biped walking motion, and the proposed formulations will be demonstrated for proof-of-concepts using gait simulation and analysis. The PGM is associated with the optimality of natural human walking, where the passivity weight functions are proposed and incorporated in the minimization of physiologically inspired weighted actuator torques. The PGM then measures the relative contribution of the stance ankle actuation. The DGM is associated with the gait stability, and quantifies the effects of inertia in terms of the Zero-Moment Point and the ground projection of center of mass. In addition, the DGM takes into account the stance foot dimension and the relative threshold between static and dynamic walking. As examples, both human-like and robotic walking motions during single support phase are generated for a planar biped system using the passivity weights and proper gait parameters. The calculated PGM values show more passive nature of human-like walking as compared with the robotic walking. The DGM results verify the dynamic nature of normal human walking with anthropomorphic foot dimension. In general, the DGMs for human-like walking are greater than those for robotic walking. The resulting DGMs also demonstrate their dependence on the stance foot dimension as well as the walking motion; for a given walking motion, smaller foot dimension results in increased dynamicity. Future work on experimental validation and demonstration will involve actual walking robots and human subjects. The proposed results will benefit the human gait studies and the development of walking robots.

Benchmarking Bipedal Locomotion: A Unified Scheme for Humanoids, Wearable Robots, and Humans

“…A further way of assessing the energetic aspects of locomotion has been recently introduced with the concept of "passivity", defined as the ability of optimizing the use of gravity and inertia to move the body forward. The resulting Passivity Gait Measure (PGM) [14], appears to be a potential benchmark because of its practical use in robotic and human scenarios. Another aspect of efficiency is the ability of reacting promptly to an external command or perturbation, usually referred to as reaction time.…”

“…Therefore the Froude number can be taken as a compact way to describe dynamic similarity between a robot and human, irrespective to size [26]. Mummolo et al [14] recently proposed an indicator of "dynamicity", i.e. the dynamic gait measure (DGM), defined as the ability of a legged system to maintain dynamic stability while statically unbalanced, therefore useful to distinguish between ZMP-based control approaches vs. natural dynamics systems (e.g.…”

Stability of Mina v2 for Robot-Assisted Balance and Locomotion

“…Its powered plantar flexion allows the human operator to navigate various environments, such as stairs and ramps, as demonstrated during the 2016 Cybathlon competition, and to reliably achieve a conservative walking speed of 0.29 m/s (Griffin et al, 2017 ). These recent advancements could progress toward robot-assisted gait that requires reduced effort from the user (Griffin et al, 2017 ) and has desired dynamic walking characteristics, e.g., similar to normal or load-carrying human walking (Mummolo and Kim, 2013 ; Mummolo et al, 2013 , 2016 ). The effort of translating human locomotion principles into robotic solutions requires quantitative benchmarks to evaluate the human-like performance of robotic assistive devices (Neuhaus et al, 2011 ).…”

Energy expenditure of a biped walking robot: instantaneous and degree-of-freedom-based instrumentation with human gait implications

“…Mathematical models of robotic EE are usually functions of kinematic (joint angles and velocities or center of mass velocity) and dynamic (joint torques or ground reaction forces) variables. While mathematical models of EE can be used for prediction, simulation, and optimization of EE for robotic systems, incomplete proxies are often used in the literature, such as actuator torques or squared actuator torques, 10,11 mechanical energy or work, 12,13 and their combinations with other terms, 4,14 which are overly simplified and do not accurately quantify the actual EE. For instance, mechanical energy, work, or their rates of change alone do not fully characterize the EE, particularly during phases of negative or zero mechanical work.…”

“…Biped walking is a common human task, and normal human walking is commonly characterized as passive dynamic walking, [31][32][33][34] in which humans tend to choose a gait that minimizes EE 35 at the expense of static instability. 11 Since robotic walking is inspired by that of humans, benchmarking human gait to resolve the conflict between stability and energetic efficiency is a logical approach. 36 For instance, an energy-related passivity index was introduced and its inverse relationship with a stability index was compared between robotic and human walking.…”