Task-relevant roadmaps: A framework for humanoid motion planning

To plan complex motions of robots with many degrees of freedom, our novel, very flexible framework builds task-relevant roadmaps (TRMs), using a new sampling-based optimizer called Natural Gradient Inverse Kinematics (NGIK) based on natural evolution strategies (NES). To build TRMs, NGIK iteratively optimizes postures covering task-spaces expressed by arbitrary task-functions, subject to constraints expressed by arbitrary cost-functions, transparently dealing with both hard and soft constraints. TRMs are grown to maximally cover the task-space while minimizing costs. Unlike Jacobian-based methods, our algorithm does not rely on calculation of gradients, making application of the algorithm much simpler. We show how NGIK outperforms recent related sampling algorithms. A video demo (http://youtu.be/N6x2e1Zf_yg) successfully applies TRMs to an iCub humanoid robot with 41 DOF in its upper body, arms, hands, head, and eyes. To our knowledge, no similar methods exhibit such a degree of flexibility in defining movements.

[1]  W. Wolovich,et al.  A computational technique for inverse kinematics , 1984, The 23rd IEEE Conference on Decision and Control.

[2]  Siddhartha S. Srinivasa,et al.  Task Space Regions , 2011, Int. J. Robotics Res..

[3]  Tom Schaul,et al.  Exponential natural evolution strategies , 2010, GECCO '10.

[4]  Oussama Khatib,et al.  A whole-body control framework for humanoids operating in human environments , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[5]  Steven M. LaValle,et al.  Planning algorithms , 2006 .

[6]  Howie Choset,et al.  Principles of Robot Motion: Theory, Algorithms, and Implementation ERRATA!!!! 1 , 2007 .

[7]  Marcelo Kallmann,et al.  A skill-based motion planning framework for humanoids , 2010, 2010 IEEE International Conference on Robotics and Automation.

[8]  Jeffrey C. Lagarias,et al.  Convergence Properties of the Nelder-Mead Simplex Method in Low Dimensions , 1998, SIAM J. Optim..

[9]  Michael Kauschke,et al.  Closed form solutions applied to redundant serial link manipulators , 1996 .

[10]  Tom Schaul,et al.  Natural Evolution Strategies , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[11]  Julia Badger,et al.  Towards Autonomous Operation of Robonaut 2 , 2012, Infotech@Aerospace.

[12]  Max Suell Dutra,et al.  New technique for inverse kinematics problem using Simulated Annealing , 2008 .

[13]  A. Hemami,et al.  A more general closed-form solution to the inverse kinematics of mechanical arms , 1987, Adv. Robotics.

[14]  Rajeev Motwani,et al.  Path Planning in Expansive Configuration Spaces , 1999, Int. J. Comput. Geom. Appl..

[15]  B. Faverjon,et al.  Probabilistic Roadmaps for Path Planning in High-Dimensional Con(cid:12)guration Spaces , 1996 .

[16]  Nikolaos G. Tsagarakis,et al.  iCub: the design and realization of an open humanoid platform for cognitive and neuroscience research , 2007, Adv. Robotics.

[17]  Siddhartha S. Srinivasa,et al.  Manipulation planning on constraint manifolds , 2009, 2009 IEEE International Conference on Robotics and Automation.

[18]  Nicolas Courty,et al.  Inverse Kinematics Using Sequential Monte Carlo Methods , 2008, AMDO.

[19]  Héctor H. González-Baños,et al.  Multi-modal Motion Planning for a Humanoid Robot Manipulation Task , 2007, ISRR.

[20]  Charles W. Wampler,et al.  Manipulator Inverse Kinematic Solutions Based on Vector Formulations and Damped Least-Squares Methods , 1986, IEEE Transactions on Systems, Man, and Cybernetics.

[21]  Jürgen Leitner,et al.  The Modular Behavioral Environment for Humanoids and other Robots (MoBeE) , 2012, ICINCO.

[22]  Victor Ng-Thow-Hing,et al.  Randomized multi-modal motion planning for a humanoid robot manipulation task , 2011, Int. J. Robotics Res..

[23]  Chris Hecker,et al.  Real-time motion retargeting to highly varied user-created morphologies , 2008, SIGGRAPH 2008.

[24]  Jean-Claude Latombe,et al.  On the Probabilistic Foundations of Probabilistic Roadmap Planning , 2006, Int. J. Robotics Res..

[25]  Stefan Schaal,et al.  STOMP: Stochastic trajectory optimization for motion planning , 2011, 2011 IEEE International Conference on Robotics and Automation.

[26]  Ronan Boulic,et al.  An inverse kinematics architecture enforcing an arbitrary number of strict priority levels , 2004, The Visual Computer.

[27]  Samuel R. Buss,et al.  Selectively Damped Least Squares for Inverse Kinematics , 2005, J. Graph. Tools.

[28]  Nikolaos V. Sahinidis,et al.  Derivative-free optimization: a review of algorithms and comparison of software implementations , 2013, J. Glob. Optim..

[29]  M. A. Zohdy,et al.  Robust Control of Robotic Manipulators , 1989, 1989 American Control Conference.