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@PhdThesis{yalov-phd, 
author = {Sharon Yalov-Handzel}, 
title = {Stable Humanoid Whole Body Motion Generation}, 
school = {{B}ar {I}lan {U}niversity}, 
year = {2016}, 
  wwwnote = {}, 
OPTannote = {} ,
  abstract = {The stability of humanoids is fragile
  and depends on the robot dynamics which are difficult
  to plan in advance. Keeping humanoids stable along
  their non-repetitive motion sequences is a great challenge
  in robotics, and it is usually resolved by using
  feedback control to consider the dynamic impacts. Off-line
  planning of whole body stable motion cannot be resolved
  by motion generators based on feedback control. We 
  propose an algorithm to plan stable whole body postures,
  based on an IKP (Inverse Kinematics Problem) solver.
  The IKP is extended to solve the kinematic
  equations under any condition that can be represented
  in geometrical form. Such a condition is the robot
  stability. This numerical iterative algorithm can be
  applied to any robot structure. In addition, the algorithm
  can find a kinematic solution that obey a certain
  optimization criteria, but is not complete. In order to
  cope with the algorithm's incompleteness, we propose
  some improvements that increase the convergence
  probability of the solution. The algorithm was analyzed
  and simulated and the core contribution of this work
  is that it gives a general method for off-line planning
  of complex postures applied to high DOF (degrees of freedom) robots
  that should obey some condition. Moreover, the improvements
  demonstrate that there is a tradeoff between the completeness
  and the generality of the solver.
 },
}