Human-Derived Disturbance Estimation and Compensation (DEC) Method Lends Itself to a Modular Sensorimotor Control in a Humanoid Robot

Abstract

The high complexity of the human posture and movement control system represents challenges for diagnosis, therapy, and rehabilitation of neurological patients. We envisage that engineering-inspired, model-based approaches will help to deal with the high complexity of the human posture control system. Since the methods of system identification and parameter estimation are limited to systems with only a few DoF, our laboratory proposes a heuristic approach that step-by-step increases complexity when creating a hypothetical human-derived control systems in humanoid robots. This system is then compared with the human control in the same test bed, a posture control laboratory. The human-derived control builds upon the identified disturbance estimation and compensation (DEC) mechanism, whose main principle is to support execution of commanded poses or movements by compensating for external or self-produced disturbances such as gravity effects. In previous robotic implementation, up to 3 interconnected DEC control modules were used in modular control architectures separately for the sagittal plane or the frontal body plane and successfully passed balancing and movement tests. In this study we hypothesized that conflict-free movement coordination between the robot's sagittal and frontal body planes emerges simply from the physical embodiment, not necessarily requiring a full body control. Experiments were performed in the 14 DoF robot Lucy Posturob (i) demonstrating that the mechanical coupling from the robot's body suffices to coordinate the controls in the two planes when the robot produces movements and balancing responses in the intermediate plane, (ii) providing quantitative characterization of the interaction dynamics between body planes including frequency response functions (FRFs), as they are used in human postural control analysis, and (iii) witnessing postural and control stability when all DoFs are challenged together with the emergence of inter-segmental coordination in squatting movements. These findings represent an important step toward controlling in the robot in future more complex sensorimotor functions such as walking.

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

“…Such sensory interrelations between body segments inspired the concept of a modular control architecture consisting of a net of interconnected DEC control modules, one for each DoF in the three planes of the human body (sagittal, frontal, horizontal; Lippi et al, 2013 ). Proof-of-principle tests in human-inspired robots were positive and, in addition, revealed functional emergencies such as an inter-segmental hip-ankle coordination (Hettich et al, 2014 ; Lippi and Mergner, 2017 ). In this architecture, a shift of activity from “ankle strategy” to “hip strategy” (see below) or, for example, from a pain-blocked knee to the neighboring joints when walking, occurs per default .…”

“…Modeling and simulating human experimental results per se may have limited value in face of the high complexity of the human posture control and the many unknown factors such as sensor and actuation noise and inaccuracies. Implementing and testing the DEC model in human-inspired robots were performed for proof of principle and demonstration of “real world” robustness of the modeling results (Mergner et al, 2009 ; Mergner, 2010 ; Hettich et al, 2014 ; Lippi and Mergner, 2017 ). From this approach, progress for posture control of both humans and robots can be expected, and the same applies to testing alternative posture control concepts in the same robot (Alexandrov et al, 2017 ) and to testing of a given control concept on different robots (Ott et al, 2016 ).…”

“…To this end, we suggest superimposing such voluntary movements on concurrent SS tilts with different waveforms (Figure 2F ; compare example in Figure 5B ). In principle, the suggested tests (Figures 2A–C,E,F ) can, in addition to the sagittal plane, also be performed in the frontal plane or some intermediate plane using the same testbed (compare Lippi and Mergner, 2017 ). However, interpretation is more difficult due to several factors such as the more efficient, yet also more complex body mechanics in these planes and a strong dependance on the legs’ stand-width, as demonstrated for humans (Goodworth and Peterka, 2010 ).…”

“…Considering benchmarking of human-like versatility and robustness for humanoid robots meets already existing fruitful interrelations between the respective human and robotics research fields. For example, while robotics seeks inspiration from humans for robots (e.g., Pfeifer et al, 2007 ), researchers of human postural control have tested their concepts in robots for proof of principle and “real world” robustness in face of noisy and inaccurate sensors and actuation (e.g., Mergner et al, 2009 ; Mergner, 2010 ; Hettich et al, 2014 ; Lippi and Mergner, 2017 ). The tests suggested for benchmarking in Figure 2 and Table 1 have all been used in human posture control experiments and some of them also in robot experiments (see Appendix).…”

Study of Postural Adjustments for Humanoidal Helpmates

“…This problem is treated from different perspectives, some works use neurobiological inspiration [4,14], other researchers are applying the pure theoretical approach [7,11,19,22,23], or the human postural data are considered [3,18]. It can be noticed that inverted pendulum models are often used as simpli ied descriptions of human body dynamics [1,7,8,12,15,19] allowing the investigation of postural stability measures.…”