Good Posture, Good Balance: Comparison of Bioinspired and Model-Based Approaches for Posture Control of Humanoid Robots

This article provides a theoretical and thorough experimental comparison of two distinct posture control approaches: (1) a fully model-based control approach and (2) a biologically inspired approach derived from human observations. While the robotic approach can easily be applied to balancing in three-dimensional (3-D) and multicontact (MC) situations, the biologically inspired balancer currently only works in two-dimensional situations but shows interesting robustness properties under time delays in the feedback loop. This is an important feature when considering the signal transmission and processing properties in the human sensorimotor system. Both controllers were evaluated in a series of experiments with a torque-controlled humanoid robot (TORO). This article concludes with some suggestions for the improvement of model-based balancing approaches in robotics.

[1]  Kazuhito Yokoi,et al.  Biped walking pattern generation by using preview control of zero-moment point , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[2]  Rieko Osu,et al.  Integration of multi-level postural balancing on humanoid robots , 2009, 2009 IEEE International Conference on Robotics and Automation.

[3]  Thomas Mergner,et al.  Vestibular humanoid postural control , 2009, Journal of Physiology-Paris.

[4]  Jun Morimoto,et al.  CB: A Humanoid Research Platform for Exploring NeuroScience , 2006, 2006 6th IEEE-RAS International Conference on Humanoid Robots.

[5]  Georg Hettich,et al.  Stability analysis of human stance control from the system theoretic point of view , 2014, 2014 European Control Conference (ECC).

[6]  Patrick J. Loughlin,et al.  Stiffness and Damping in Postural Control Increase With Age , 2010, IEEE Transactions on Biomedical Engineering.

[7]  Johannes Englsberger,et al.  On the inertially decoupled structure of the floating base robot dynamics , 2015 .

[8]  Kai Hu,et al.  Online iterative learning control of zero-moment point for biped walking stabilization , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[9]  Youngjin Choi,et al.  Posture/Walking Control for Humanoid Robot Based on Kinematic Resolution of CoM Jacobian With Embedded Motion , 2007, IEEE Transactions on Robotics.

[10]  M. Vukobratovic,et al.  On the stability of anthropomorphic systems , 1972 .

[11]  Alexander A. Frolov,et al.  Biomechanical analysis of movement strategies in human forward trunk bending. I. Modeling , 2001, Biological Cybernetics.

[12]  Stefan Schaal,et al.  Optimal distribution of contact forces with inverse-dynamics control , 2013, Int. J. Robotics Res..

[13]  Alin Albu-Schäffer,et al.  Overview of the torque-controlled humanoid robot TORO , 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.

[14]  Bruno Siciliano,et al.  Six-DOF impedance control based on angle/axis representations , 1999, IEEE Trans. Robotics Autom..

[15]  Dennis W. Hong,et al.  Two configurations of series elastic actuators for linearly actuated humanoid robots with large range of motion , 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.

[16]  Thomas Mergner,et al.  A neurological view on reactive human stance control , 2010, Annu. Rev. Control..

[17]  Georg Hettich,et al.  Human hip-ankle coordination emerging from multisensory feedback control. , 2014, Human movement science.

[18]  Alexander Herzog,et al.  Momentum control with hierarchical inverse dynamics on a torque-controlled humanoid , 2014, Autonomous Robots.

[19]  Gordon Cheng,et al.  Full-Body Compliant Human–Humanoid Interaction: Balancing in the Presence of Unknown External Forces , 2007, IEEE Transactions on Robotics.

[20]  Hirochika Inoue,et al.  Real-time humanoid motion generation through ZMP manipulation based on inverted pendulum control , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[21]  Marjorie H. Woollacott,et al.  Aging and Posture Control: Changes in Sensory Organization and Muscular Coordination , 1986, International journal of aging & human development.

[22]  Joohyung Kim,et al.  Development of the lower limbs for a humanoid robot , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[23]  F E Zajac,et al.  Human standing posture: multi-joint movement strategies based on biomechanical constraints. , 1993, Progress in brain research.

[24]  T. Mergner,et al.  Multisensory control of human upright stance , 2006, Experimental Brain Research.

[25]  Gerd Hirzinger,et al.  Posture and balance control for biped robots based on contact force optimization , 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

[26]  Vittorio Lippi,et al.  A Bio-inspired Modular System for Humanoid Posture Control , 2021, ArXiv.

[27]  R. Peterka Sensorimotor integration in human postural control. , 2002, Journal of neurophysiology.

[28]  A. Kuo An optimal state estimation model of sensory integration in human postural balance , 2005, Journal of neural engineering.

[29]  Christian Ott,et al.  Control applications of TORO — A Torque controlled humanoid robot , 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.