@phdthesis{oai:tsukuba.repo.nii.ac.jp:00008681,
 author = {Takeuchi, Hiroki and 竹内, 裕喜},
 month = {},
 note = {Robot movement generation requires optimization treatment. However, the need for off-line computation makes it difficult to apply traditional optimization techniques to real-time robot control. An important goal is to develop a new algorithm that allows for real-time optimization. The most likely candidate which is called as Receding Horizon Control or Model Predictive Control algorithms have yet to be widely applied to real-time robot control environments. This thesis uses a legged robots as a control object, one that possesses unstable dynamics and requires specific balance conditions, with the Zero Moment Point balance condition being a particulary important challenge. Equal constraint, proposed in this thesis as a means for meeting such conditions during optimization formulation, overcomes Zero Moment Point problems. The state variable inequality constraint is a complex challenge because the optimal path must tangentially enter a constrained arc, and one or more time constraint derivatives must equal zero at all entry points. A second challenge addressed in this thesis is the description of a legged robot's swing leg condition as a state variable inequality. Both the nonlinear swing leg and Zero Moment Point balance conditions are involved Receding Horizon Control formulation.  ･･･, 2004, Includes bibliographical references, Includes supplementary treatises},
 school = {筑波大学, University of Tsukuba},
 title = {Real-time generation for optimal robot motion},
 year = {2005}
}