Title :
Task-relevant roadmaps: A framework for humanoid motion planning
Author :
Marijn Stollenga;Leo Pape;Mikhail Frank;Jurgen Leitner;Alexander Forster;Jurgen Schmidhuber
Author_Institution :
Dalle Molle Inst. for Artificial Intell. (IDSIA)/SUPSI, Univ. della Svizzera Italiana (USI), Lugano, Switzerland
Abstract :
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.
Keywords :
"Kinematics","Planning","Optimization","Humanoid robots","Transmission line measurements","Robot kinematics"
Conference_Titel :
Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on
Electronic_ISBN :
2153-0866
DOI :
10.1109/IROS.2013.6697192