@InProceedings{ayusawa:iros:2019,
  author    = {Ayusawa, Ko and Suleiman, Wael and Yoshida, Eiichi},
  title     = {Predictive Inverse Kinematics: Optimizing Future Trajectory through Implicit Time Integration and Future Jacobian Estimation},
  booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year      = {2019},
  pages     = {566--573},
  address   = {Macau,China},
  month     = {November 4-November 8},
  url       = {https://staff.aist.go.jp/k.ayusawa/pdf/Ayusawa\_2019\_IROS.pdf},
  keywords  = {inverse kinematics, motion optimization, comprehensive motion transformation, implicit time integration, predictive control, humanoid},
  doi       = {10.1109/IROS40897.2019.8968110},
  abstract  = {This paper presents an inverse kinematics (IK) method which can control future velocities and accelerations for multi-body systems. The proposed IK method is formulated as a quadratic programing (QP) that optimizes future joint trajectories. The features of the proposed IK are: (1) the evaluation of accelerations at future time instances, (2) the trajectory representation that can implicitly integrate the time integralformulaintoQP,(3)thecomputationoffutureJacobian matrices based on the comprehensive theory of differential kinematics proposed in our previous work. Those features enable a stable and fast IK computation while evaluating the future accelerations. We also conducted thorough numerical studies to show the efficiency of the proposed method.}
}