研 究 生:謝忠豫 指導老師:王明賢教授 報告日期 : 2011/01/07

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研 究 生:謝忠豫 指導老師:王明賢教授 報告日期 : 2011/01/07 Boundary Condition Relaxation Method for Stepwise Pedipulation Planning of Biped Robots SOURCE FROM : IEEE TRANSACTIONS ON ROBOTICS, VOL. 25, NO. 3, JUNE 2009 pp658-669 作者 : Tomomichi Sugihara, Member, IEEE, and Yoshihiko Nakamura, Member, IEEE 研 究 生:謝忠豫 指導老師:王明賢教授 報告日期 : 2011/01/07

Abstract pedipulation planning method legged motion online motion planning

I. INTRODUCTION 1. Zero-Moment Point (ZMP) 2. Center-Of-Mass (COM) 3. mass-concentrated model

It is realized by the boundary condition relaxation in the sense that: 1) it accepts a certain level of error at the goal state from the desired values since such an error is not critical for achievement of biped motions in most situations and 2) it permits discontinuity of the ZMP trajectory, which is defined from the equilibrium between inertial force and reaction force.

II. COM TRAJECTORY PLANNING VIA BOUNDARY CONDITION RELAXATION A. Formulation of the Analytical Approach Based on Mass-Concentrated Model B. ZMP Trajectory Function for Rapid Stance Foot Alternation C. Boundary Condition Relaxation Method 少了一張

III. SEMIAUTOMATIC PEDIPULATION PLANNING FROM FOOT PLACEMENT COMMAND

IV. INVERSE KINEMATICS INCLUDING COM COM Jacobian matrix

V. EXAMPLE OF MOTION PLANNING AND EXPERIMENTS center of rotation (COR)

PID控制 Σ 1.類比控制的PID演算法 de u(t)=Kpe(t)+Ki∫e(t)dt+Kd dt 2.數位控制的PID演算法 t 2.數位控制的PID演算法 u(nT)=Kpe(KT)+Σe(jT)+Kd[e(KT)-e((K-1)T] j=0 k Kp 改 e(k) Σ u(k) Ki∫ dt Kd 圖. PID控制的基本架構

(a) Loci in time domain on x-axis. Planned trajectory of COM(xG ,yG ), feet(xK ,yK ,xS ,yS ), and ZMP(xZ ,yZ ) of the walking motion. (a) Loci in time domain on x-axis.

VI. CONCLUSION presented a fast stepwise pedipulation planning method for biped robots based on the analytical solution of the equation of motion of an approximate mass-concentrated model. It has the following advantages. Position–velocity continuity at the initial time and the reaction force constraint are simultaneously satisfied by relaxing the boundary condition at the goal, namely, accepting a certain level of error from the desired state. 2) The planning completes in one interval by permitting discontinuity of ZMP. It facilitates responsive motion planning such as sudden starting, turning, and stopping online.

REFERENCES [1] F. Kanehiro, M. Inaba, and H. Inoue, “Action acquisition framework for humanoid robots based on kinematics and dynamics adaptation,” in Proc.1999 IEEE Int. Conf. Robot. Autom., pp. 1038–1043. [2] S. Kagami, T. Kitagawa, K. Nishiwaki, T. Sugihara, M. Inaba, and H. Inoue, “A fast dynamically equilibrated walking trajectory generation method of humanoid robot,” Auton. Robots, vol. 12, no. 1, pp. 71–82,2002. [3] M. Vukobratovi´c and J. Stepanenko, “On the stability of anthropomorphic systems,” Math. Biosci., vol.15, no. 1, pp. 1–37, 1972. [4] S. Kitamura, Y. Kurematsu, and M. Iwata, “Motion generation of a biped locomotive robot using an inverted pendulum model and neural networks,” in Proc. 29th IEEE Conf. Decis. Control, 1990, vol. 6, pp. 3308–3312. [5] S. Kagami, T. Kitagawa, K. Nishiwaki, T. Sugihara, M. Inaba, and H. Inoue, “A fast dynamically equilibrated walking trajectory generation method of humanoid robot,” Auton. Robots, vol. 12, no. 1, [6] M. Vukobratovi´c and J. Stepanenko, “On the stability of anthropomorphic systems,” Math. Biosci., vol. 15, no. 1, pp. 1–37, 1972. [7] K. Nishiwaki, S. Kagami, J. J. Kuffner, M. Inaba, and H. Inoue, “Online humanoid walking control system and a moving goal tracking experiment,”in Proc. 2003 IEEE Int. Conf.Robot. Autom., pp. 911–916.

REFERENCES [8] K. Harada, S. Kajita, K. Kaneko, and H. Hirukawa, “An analytical method on real-time gait planning for a humanoid robot,” in Proc. 2004 IEEERAS/RSJ Int. Conf. Humanoid Robots, Nov. 10–12, vol. 2, pp. 640–655. [9] F.Yamasaki,K. Endo, H. Kitano, and M.Asada, “Acquisition of humanoid walking motion using genetic algorithm—considering characteristics of servo modules,” in Proc. 2002 IEEE Int. Conf. Robot. Autom., pp. 3123–3128.