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Sharon Yalov-Handzel. ** Stable Humanoid Whole Body Motion Generation**. Ph.D. Thesis, Bar Ilan University, 2016.

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.

@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. }, }

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