A Fast Online Gait Planning with Boundary Condition Relaxation for Humanoid Robots

Sugihara, Tomomichi; Nakamura, Yoshihiko

doi:10.1109/robot.2005.1570136

Cited by 83 publications

(64 citation statements)

References 13 publications

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“…Several biped control methods have been proposed and applied to humanoid robots (Hirai et al 1998;Kajita et al 2007;Nagasaka et al 1999Nagasaka et al , 2004Sugihara and Nakamura 2005). Most of them use ZMP-based walking controllers.…”

Section: Application To Other Walking Controllersmentioning

confidence: 99%

Nonparametric representation of an approximated Poincaré map for learning biped locomotion

Morimoto

Atkeson

2009

Auton Robot

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We propose approximating a Poincaré map of biped walking dynamics using Gaussian processes. We locally optimize parameters of a given biped walking controller based on the approximated Poincaré map. By using Gaussian processes, we can estimate a probability distribution of a target nonlinear function with a given covariance. Thus, an optimization method can take the uncertainty of approximated maps into account throughout the learning process. We use a reinforcement learning (RL) method as the optimization method. Although RL is a useful non-linear optimizer, it is usually difficult to apply RL to real robotic systems due to the large number of iterations required to acquire suitable policies. In this study, we first approximated the Poincaré map by using data from a real robot, and then applied RL using the estimated map in order to optimize stepping and walking policies. We show that we can improve stepping and walking policies both in simulated and real environments. Experimental validation on a humanoid robot of the approach is presented.

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Section: Application To Other Walking Controllersmentioning

confidence: 99%

Nonparametric representation of an approximated Poincaré map for learning biped locomotion

Morimoto

Atkeson

2009

Auton Robot

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“…To generate a motion pattern in realtime, the inverted pendulum model which is represented as the linear differential equation is derived by an approximate dynamics of COG [13]- [16]. Kagami [13] realizes a fast generation of dynamically stable humanoid robot walking pattern by digitalizing the differential equation.…”

Section: Related Workmentioning

confidence: 99%

“…Although the generation method of biped walking pattern by using preview control which is proposed by Kajita [14] can be satisfy the boundary condition, it is difficult to guarantee stable stop motion because it is not clear to relate between the initial value of state variables and the ZMP tracking error. Harada [15] and Sugihara [16] generated a real-time biped gait using an analytical solution. In these methods, the relation to the displacement of ZMP and the initial value is also unclear.…”

Section: Related Workmentioning

confidence: 99%

Motion Planning of Emergency Stop for Humanoid Robot by State Space Approach

Morisawa¹,

Kaneko²,

Kanehiro³

et al. 2006

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-A motion planner of emergency stop must make an operating humanoid robot to a stationary state under the emergency signal. It plays an important role in prevention of falling over because humanoid robots fall over easily. Immediately after the emergency signal, it must generate the emergency stop motion in real-time. We modeled a humanoid robot as a simple dynamic system consists of ZMP (Zero-Moment Point) and COG (Center of Gravity) as its states. The emergency stop motion is generated by a state feedback. We determined optimal feedback gains in terms of the initial conditions and the pole assignment. The proposed method realized a reliable emergency stop with low computational cost. Furthermore, it can easily predict the possibility of the successful emergency stop at any time. The validity of the proposed method is confirmed by an experiment using humanoid robot HRP-2.

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“…Because the inverted pendulum model effectively reflects the dominant dynamics of the walking motion, many successful results have been reported [1][2][3][4]. Other approaches reduce the complexity of the equation of motion by assuming that the zero moment point (ZMP) trajectory has a specific form [5][6][7][8]. Several methods do not use explicit walking trajectories.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Simulation of Modifiable Walking Pattern Generation to Handle Infeasible Navigational Commands for Humanoid Robots

Hong¹,

Lee²,

Lee³

2016

Journal of Electrical Engineering and Technology

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-The modifiable walking pattern generation (MWPG) algorithm can handle dynamic walking commands by changing the walking period, step length, and direction independently. When an infeasible command is given, the algorithm changes the command to a feasible one. After the feasibility of the navigational command is checked, it is translated into the desired center of mass (CM) state. To achieve the desired CM state, a reference CM trajectory is generated using predefined zero moment point (ZMP) functions. Based on the proposed algorithm, various complex walking patterns were generated, including backward and sideways walking. The effectiveness of the patterns was verified in dynamic simulations using the Webots simulator.

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A Fast Online Gait Planning with Boundary Condition Relaxation for Humanoid Robots

Cited by 83 publications

References 13 publications

Nonparametric representation of an approximated Poincaré map for learning biped locomotion

Nonparametric representation of an approximated Poincaré map for learning biped locomotion

Motion Planning of Emergency Stop for Humanoid Robot by State Space Approach

Dynamic Simulation of Modifiable Walking Pattern Generation to Handle Infeasible Navigational Commands for Humanoid Robots

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