Idiothetic Verticality Estimation Through Head Stabilization Strategy

The knowledge of the gravitational vertical is fundamental for the autonomous control of humanoids and other free-moving robotic systems such as rovers and drones. This letter deals with the hypothesis that the so-called “head stabilization strategy” observed in humans and animals facilitates the estimation of the true vertical from inertial sensing only. This problem is difficult because inertial measurements respond to a combination of gravity and fictitious forces that are hard to disentangle. From simulations and experiments, we found that the angular stabilization of a platform bearing inertial sensors enables the application of the separation principle. This principle, which permits one to design estimators and controllers independently from each other, typically applies to linear systems, but rarely to nonlinear systems. We found empirically that, given inertial measurements, the angular regulation of a platform results in a system that is stable and robust and which provides true vertical estimates as a byproduct of the feedback. We conclude that angularly stabilized inertial measurement platforms could liberate robots from ground-based measurements for postural control, locomotion, and other functions, leading to a true idiothetic sensing modality, that is, not based on any external reference but the gravity field.

[1]  Vincent Hayward,et al.  Gravito-inertial ambiguity resolved through head stabilization , 2019, Proceedings of the Royal Society A.

[2]  Paolo Dario,et al.  Head stabilization based on a feedback error learning in a humanoid robot , 2012, 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication.

[3]  Alexander P. Krishchenko,et al.  SEPARATION PRINCIPLE FOR A CLASS OF NONLINEAR SYSTEMS , 2002 .

[4]  Rodney A. Brooks The Cog Project , 1997 .

[5]  Vincent Hayward,et al.  Modeling Verticality Estimation During Locomotion , 2013 .

[6]  A. Berthoz,et al.  Head stabilization during various locomotor tasks in humans , 2004, Experimental Brain Research.

[7]  Tamim Asfour,et al.  Toward humanoid manipulation in human-centred environments , 2008, Robotics Auton. Syst..

[8]  Vincent Hayward,et al.  On the benefits of head stabilization with a view to control balance and locomotion in humanoids , 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

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

[10]  Norman M. Wereley,et al.  Visual, vestibular and voluntary contributions to human head stabilization , 2004, Experimental Brain Research.

[11]  Jun Morimoto,et al.  The eMOSAIC model for humanoid robot control , 2012, Neural Networks.

[12]  Alain Berthoz,et al.  Head-eyes system and gaze analysis of the humanoid robot Romeo , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  A M Bronstein,et al.  The perception of body verticality (subjective postural vertical) in peripheral and central vestibular disorders. , 1996, Brain : a journal of neurology.

[14]  D. Angelaki,et al.  Vestibular system: the many facets of a multimodal sense. , 2008, Annual review of neuroscience.

[15]  Etienne Burdet,et al.  Assisting Human Balance in Standing With a Robotic Exoskeleton , 2019, IEEE Robotics and Automation Letters.

[16]  R. Brooks,et al.  The cog project: building a humanoid robot , 1999 .

[17]  D. Luenberger Observing the State of a Linear System , 1964, IEEE Transactions on Military Electronics.

[18]  Chang-Woo Park,et al.  Local Separation Principle for a Special Class of Nonlinear Systems , 2007 .

[19]  Nikolaos G. Tsagarakis,et al.  The Design of the iCub humanoid Robot , 2012, Int. J. Humanoid Robotics.

[20]  Jean-Paul Laumond,et al.  Contribution of actuated head and trunk to passive walkers stabilization , 2013, 2013 IEEE International Conference on Robotics and Automation.

[21]  A. Berthoz,et al.  Head and trunk movements in the frontal plane during complex dynamic equilibrium tasks in humans , 2004, Experimental Brain Research.

[22]  A. Berthoz,et al.  Eye-head coordination for the steering of locomotion in humans: an anticipatory synergy , 1998, Neuroscience Letters.

[23]  Paolo Dario,et al.  Head stabilization in a humanoid robot: models and implementations , 2016, Autonomous Robots.

[24]  N. McClamroch,et al.  Rigid-Body Attitude Control , 2011, IEEE Control Systems.

[25]  A. Takanishi,et al.  Implementation of a human model for head stabilization on a humanoid platform , 2012, 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob).

[26]  Etienne Burdet,et al.  Anticipatory detection of turning in humans for intuitive control of robotic mobility assistance , 2017, Bioinspiration & biomimetics.

[27]  Paolo Dario,et al.  Adaptive gaze stabilization through cerebellar internal models in a humanoid robot , 2016, 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob).

[28]  A M Bronstein,et al.  Evidence for a vestibular input contributing to dynamic head stabilization in man. , 1988, Acta oto-laryngologica.

[29]  Vincent Hayward,et al.  Review of Anthropomorphic Head Stabilisation and Verticality Estimation in Robots , 2018, Biomechanics of Anthropomorphic Systems.