Generation of dynamic humanoid behaviors through task-space control with conic optimization

This paper presents a new formulation of prioritized task-space control for humanoids that is used to develop a dynamic kick and dynamic jump in a 26 degree of freedom simulated system. The demonstrated motions are controlled through a real-time conic optimization scheme that selects appropriate joint torques and contact forces. More specifically, motions are characterized in appropriate task spaces, and the real-time optimizer solves the task-space control problem while accounting for user-defined priorities between the tasks. In contrast to previous solutions of the Prioritized Task-Space Control (PTSC) problem for humanoids, the solution presented here satisfies the ZMP constraint and ground friction limitations at all levels of priority, and is general to periods of flight as well as support. All generated motions include control of the system's centroidal angular momentum, which leads to emergent whole-body behaviors, such as arm-swing, that are not specified by the designer. In addition, compared to a previous quadratic programming solution of the PTSC problem, our approach gains a factor of 2 speedup in its required computational time. This speedup allows the control approach to operate at real-time rates of approximately 200 Hz.

[1]  T. Crouch.  Chapter 2 – Dynamics , 1981 .

[2]  Oussama Khatib,et al.  A unified approach for motion and force control of robot manipulators: The operational space formulation , 1987, IEEE J. Robotics Autom..

[3]  Yoshihiko Nakamura,et al.  Nonholonomic path planning of space robots , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[4]  David E. Orin,et al.  DynaMechs: An Object Oriented Software Package for Efficient Dynamic Simulation of Underwater Robotic Vehicles , 1995 .

[5]  Jessica K. Hodgins,et al.  Simulating leaping, tumbling, landing and balancing humans , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[6]  Erling D. Andersen,et al.  On implementing a primal-dual interior-point method for conic quadratic optimization , 2003, Math. Program..

[7]  Katsu Yamane,et al.  Dynamics Filter - concept and implementation of online motion Generator for human figures , 2000, IEEE Trans. Robotics Autom..

[8]  Oussama Khatib,et al.  Contact consistent control framework for humanoid robots , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[9]  Blake M. Ashby,et al.  Optimal control simulations reveal mechanisms by which arm movement improves standing long jump performance. , 2006, Journal of biomechanics.

[10]  Roy Featherstone,et al.  Rigid Body Dynamics Algorithms , 2007 .

[11]  Frank Chongwoo Park,et al.  Convex Optimization Algorithms for Active Balancing of Humanoid Robots , 2007, IEEE Transactions on Robotics.

[12]  David E. Orin,et al.  Centroidal Momentum Matrix of a humanoid robot: Structure and properties , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Jovan Popovic,et al.  Simulation of Human Motion Data using Short‐Horizon Model‐Predictive Control , 2008, Comput. Graph. Forum.

[14]  Demetri Terzopoulos,et al.  Biomechanical modeling and control of the human body for computer animation , 2008 .

[15]  Victor B. Zordan,et al.  Momentum control for balance , 2009, ACM Trans. Graph..

[16]  Katsu Yamane,et al.  Control-aware mapping of human motion data with stepping for humanoid robots , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[17]  David E. Orin,et al.  Whole-body humanoid control from upper-body task specifications , 2010, 2010 IEEE International Conference on Robotics and Automation.

[18]  Martin de Lasa,et al.  Feature-based locomotion controllers , 2010, ACM Trans. Graph..

[19]  Aaron Hertzmann,et al.  Feature-based locomotion controllers , 2010, SIGGRAPH 2010.

[20]  Oussama Khatib,et al.  Compliant Control of Multicontact and Center-of-Mass Behaviors in Humanoid Robots , 2010, IEEE Transactions on Robotics.

[21]  Stefan Schaal,et al.  Inverse dynamics control of floating base systems using orthogonal decomposition , 2010, 2010 IEEE International Conference on Robotics and Automation.

[22]  Sung-Hee Lee,et al.  Fall on Backpack: Damage Minimizing Humanoid Fall on Targeted Body Segment Using Momentum Control , 2011 .

[23]  Vincent Padois,et al.  Synthesis of complex humanoid whole-body behavior: A focus on sequencing and tasks transitions , 2011, 2011 IEEE International Conference on Robotics and Automation.

[24]  Stefan Schaal,et al.  Control of legged robots with optimal distribution of contact forces , 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

[25]  Nicolas Mansard,et al.  A dedicated solver for fast operational-space inverse dynamics , 2012, 2012 IEEE International Conference on Robotics and Automation.

[26]  David E. Orin,et al.  A reduced-order recursive algorithm for the computation of the operational-space inertia matrix , 2012, 2012 IEEE International Conference on Robotics and Automation.

[27]  Joseph Salini,et al.  Dynamic control for the task/posture coordination of humanoids: Toward synthesis of complex activities , 2014 .