著者

原田 祐志 浅野 文彦 田地 宏一 宇野 洋二

出版者

一般社団法人 日本ロボット学会

雑誌

日本ロボット学会誌 (ISSN:02891824)

巻号頁・発行日

vol.27, no.5, pp.575-582, 2009 (Released:2011-11-15)

参考文献数

9

被引用文献数

3 2

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We have applied a parametric excitation method to a kneed biped robot with semicircular feet and have shown that the robot can walk sustainably with only knee torque. A swing-leg of the kneed biped robot has similar mechanism to an acrobot, and many acrobots are controlled in inverse direction like ornithoid walking. These suggest that inverse bending of a knee restores more mechanical energy than forward bending, and hence, the ornithoid walking can be more efficient. In this paper, we first compare the forward bending with the inverse bending for a double pendulum, and show by numerical simulation that the mechanical energy of the inverse bending increases more than that of the forward bending like human walking. We then propose a parametric excitation based ornithoid gait for a kneed biped robot, and show sustainably walking by numerical simulation. Finally, we compare parametric excitation based ornithoid gait with parametric excitation based human gait, and we show that ornithoid gait is more efficeint.

著者

鈴木 脩平 田地 宏一

出版者

公益社団法人 計測自動制御学会

雑誌

計測自動制御学会論文集 (ISSN:04534654)

巻号頁・発行日

vol.50, no.4, pp.348-355, 2014 (Released:2014-04-16)

参考文献数

15

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In model predictive control (MPC), an optimal control problem is solved at each time steps to determine control input. To realize on-line control of MPC, reducing computational time is requisite. In this paper, we apply a semismooth Newton method for MPC with simple bounds. The semismooth Newton method is one of iterative methods and is used to solve a complementarity problem and a KKT system of optimization problems. The semismooth Newton method has an advantage over other QP solvers, such as interior point methods and so on, that the initial point can be chosen arbitrarily, and this enables hot start. We show that the proposed method is globally convergent. We also show the condition guaranteeing the nonsingularity of the generalized Jacobian at a solution, which is closely related to the quadratic convergence of the algorithm. This is the first result to clarify the reason why constraints on state variables make MPC computationally expensive from the algorithmic perspective. Some numerical examples show that the proposed method is practically efficient.