Bipedal Locomotion Control Based on Simultaneous Trajectory and Foot Step Planning

2016 ◽  
Vol 28 (4) ◽  
pp. 533-542 ◽  
Author(s):  
Kouta Goto ◽  
◽  
Yuichi Tazaki ◽  
Tatsuya Suzuki
Keyword(s):  
Constraint Satisfaction Problem ◽  
Center Of Mass ◽  
Bipedal Locomotion ◽  
Nonlinear Constraint ◽  
Inverted Pendulum Model ◽  
Pendulum Model ◽  
Lower Figure ◽  
Planning Methods ◽  
Real Robot ◽  
Trajectory Tracking Controller

[abstFig src='/00280004/11.jpg' width='300' text='Snapshots of a bipedal robot walking forward (upper figure) and walking sideways (lower figure)' ] This paper proposes a trajectory planner for bipedal locomotion that determines a center-of-mass (CoM) trajectory, footsteps, and step durations simultaneously. Trajectory planning based on a linear inverted pendulum model is formulated as a nonlinear constraint satisfaction problem. The proposed iterative constraint solving algorithm is able to solve this problem in a short amount of time so that trajectory replanning at every walking step is possible. Unlike existing planning methods that determine footsteps and a CoM trajectory sequentially under fixed walking period, the proposed planner can produce complex walking patterns that fully utilize the interdependency of these physical quantities. The proposed trajectory planner and a trajectory tracking controller is implemented on a real robot and their performance is evaluated.

scholarly journals Turning Gait Planning Method for Humanoid Robots

2018 ◽  
Vol 8 (8) ◽  
pp. 1257 ◽  
Author(s):  
Tianqi Yang ◽  
Weimin Zhang ◽  
Xuechao Chen ◽  
Zhangguo Yu ◽  
Libo Meng ◽  
...  
Keyword(s):  
Inverted Pendulum ◽  
Center Of Mass ◽  
Translational Motion ◽  
Humanoid Robots ◽  
Inverted Pendulum Model ◽  
Straight Line ◽  
Pendulum Model ◽  
The Stability ◽  
And Control ◽  
Present Simulation

The most important feature of this paper is to transform the complex motion of robot turning into a simple translational motion, thus simplifying the dynamic model. Compared with the method that generates a center of mass (COM) trajectory directly by the inverted pendulum model, this method is more precise. The non-inertial reference is introduced in the turning walk. This method can translate the turning walk into a straight-line walk when the inertial forces act on the robot. The dynamics of the robot model, called linear inverted pendulum (LIP), are changed and improved dynamics are derived to make them apply to the turning walk model. Then, we expend the new LIP model and control the zero moment point (ZMP) to guarantee the stability of the unstable parts of this model in order to generate a stable COM trajectory. We present simulation results for the improved LIP dynamics and verify the stability of the robot turning.

Dynamic and Reactive Walking for Humanoid Robots Based on Foot Placement Control

2016 ◽  
Vol 13 (02) ◽  
pp. 1550041 ◽  
Author(s):  
Juan Alejandro Castano ◽  
Zhibin Li ◽  
Chengxu Zhou ◽  
Nikos Tsagarakis ◽  
Darwin Caldwell
Keyword(s):  
Center Of Mass ◽  
Humanoid Robots ◽  
Gait Pattern ◽  
Gait Patterns ◽  
Foot Placement ◽  
Inverted Pendulum Model ◽  
Gait Parameters ◽  
Pendulum Model ◽  
Single Mass ◽  
Walking Velocity

This paper presents a novel online walking control that replans the gait pattern based on our proposed foot placement control using the actual center of mass (COM) state feedback. The analytic solution of foot placement is formulated based on the linear inverted pendulum model (LIPM) to recover the walking velocity and to reject external disturbances. The foot placement control predicts where and when to place the foothold in order to modulate the gait given the desired gait parameters. The zero moment point (ZMP) references and foot trajectories are replanned online according to the updated foothold prediction. Hence, only desired gait parameters are required instead of predefined or fixed gait patterns. Given the new ZMP references, the extended prediction self-adaptive control (EPSAC) approach to model predictive control (MPC) is used to minimize the ZMP response errors considering the acceleration constraints. Furthermore, to ensure smooth gait transitions, the conditions for the gait initiation and termination are also presented. The effectiveness of the presented gait control is validated by extensive disturbance rejection studies ranging from single mass simulation to a full body humanoid robot COMAN in a physics based simulator. The versatility is demonstrated by the control of reactive gaits as well as reactive stepping from standing posture. We present the data of the applied disturbances, the prediction of sagittal/lateral foot placements, the replanning of the foot/ZMP trajectories, and the COM responses.

Stabilized Walking of Humanoid NAO using Enhanced Spring-Loaded Inverted Pendulum Model on Uneven Terrain

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Path Length ◽  
Inverted Pendulum ◽  
Center Of Mass ◽  
Humanoid Robots ◽  
Slip Model ◽  
Turning Angle ◽  
Uneven Terrain ◽  
Inverted Pendulum Model ◽  
Pendulum Model ◽  
Spring Loaded Inverted Pendulum

In the coming decades, humanoid robots will play a rising role in society. The present article discusses their walking control and obstacle avoidance on uneven terrain using enhanced spring-loaded inverted pendulum model (ESLIP). The SLIP model is enhanced by tuning it with an adaptive particle swarm optimization (APSO) approach. It helps the humanoid robot to reach closer to the obstacles in order to optimize the turning angle to optimize the path length. The desired trajectory, along with the sensory data, is provided to the SLIP model, which creates compatible COM (center of mass) dynamics for stable walking. This output is fed to APSO as input, which adjusts the placement of the foot during interaction with uneven surfaces and obstacles. It provides an optimum turning angle for shunning the obstacles and ensures the shortest path length. Simulation has been carried out in a 3D simulator based on the proposed controller and SLIP controller in uneven terrain.

scholarly journals Effect of reduced gravity on the preferred walk-run transition speed.

1997 ◽  
Vol 200 (4) ◽  
pp. 821-826 ◽  
Author(s):  
R Kram ◽  
A Domingo ◽  
D P Ferris
Keyword(s):  
Froude Number ◽  
Inverted Pendulum ◽  
Center Of Mass ◽  
Reduced Gravity ◽  
Leg Length ◽  
Pendulum System ◽  
Transition Speed ◽  
Inverted Pendulum Model ◽  
Inverted Pendulum System ◽  
Pendulum Model

We investigated the effect of reduced gravity on the human walk-run gait transition speed and interpreted the results using an inverted-pendulum mechanical model. We simulated reduced gravity using an apparatus that applied a nearly constant upward force at the center of mass, and the subjects walked and ran on a motorized treadmill. In the inverted pendulum model for walking, gravity provides the centripetal force needed to keep the pendulum in contact with the ground. The ratio of the centripetal and gravitational forces (mv2/L)/(mg) reduces to the dimensionless Froude number (v2/gL). Applying this model to a walking human, m is body mass, v is forward velocity, L is leg length and g is gravity. In normal gravity, humans and other bipeds with different leg lengths all choose to switch from a walk to a run at different absolute speeds but at approximately the same Froude number (0.5). We found that, at lower levels of gravity, the walk-run transition occurred at progressively slower absolute speeds but at approximately the same Froude number. This supports the hypothesis that the walk-run transition is triggered by the dynamics of an inverted-pendulum system.

Parameterized gait pattern generator based on linear inverted pendulum model with natural ZMP references

2016 ◽  
Vol 32 ◽  
Author(s):  
Ya-Fang Ho ◽  
Tzuu-Hseng S. Li ◽  
Ping-Huan Kuo ◽  
Yan-Ting Ye
Keyword(s):  
Inverted Pendulum ◽  
Center Of Mass ◽  
Gait Pattern ◽  
Gait Patterns ◽  
Gait Planning ◽  
Inverted Pendulum Model ◽  
Pendulum Model ◽  
Lateral Plane ◽  
Planning Algorithm ◽  
Zero Moment

AbstractThis paper presents a parameterized gait generator based on linear inverted pendulum model (LIPM) theory, which allows users to generate a natural gait pattern with desired step sizes. Five types of zero moment point (ZMP) components are proposed for formulating a natural ZMP reference, where ZMP moves continuously during single support phases instead of staying at a fixed point in the sagittal and lateral plane. The corresponding center of mass (CoM) trajectories for these components are derived by LIPM theory. To generate a parameterized gait pattern with user-defined parameters, a gait planning algorithm is proposed, which determines related coefficients and boundary conditions of the CoM trajectory for each step. The proposed parameterized gait generator also provides a concept for users to generate gait patterns with self-defined ZMP references by using different components. Finally, the feasibility of the proposed method is validated by the experimental results with a teen-sized humanoid robot, David, which won first place in the sprint event at the 20th Federation of International Robot-soccer Association (FIRA) RoboWorld Cup.

scholarly journals Capture Steps: Robust Walking for Humanoid Robots

2019 ◽  
Vol 16 (06) ◽  
pp. 1950032 ◽  
Author(s):  
Marcell Missura ◽  
Maren Bennewitz ◽  
Sven Behnke
Keyword(s):  
Degrees Of Freedom ◽  
Center Of Mass ◽  
Humanoid Robots ◽  
Open Loop ◽  
Bipedal Walking ◽  
Foot Placement ◽  
Inverted Pendulum Model ◽  
Push Recovery ◽  
Pendulum Model ◽  
Walking Velocity

Stable bipedal walking is a key prerequisite for humanoid robots to reach their potential of being versatile helpers in our everyday environments. Bipedal walking is, however, a complex motion that requires the coordination of many degrees of freedom while it is also inherently unstable and sensitive to disturbances. The balance of a walking biped has to be constantly maintained. The most effective ways of controlling balance are well timed and placed recovery steps — capture steps — that absorb the expense momentum gained from a push or a stumble. We present a bipedal gait generation framework that utilizes step timing and foot placement techniques in order to recover the balance of a biped even after strong disturbances. Our framework modifies the next footstep location instantly when responding to a disturbance and generates controllable omnidirectional walking using only very little sensing and computational power. We exploit the open-loop stability of a central pattern generated gait to fit a linear inverted pendulum model (LIPM) to the observed center of mass (CoM) trajectory. Then, we use the fitted model to predict suitable footstep locations and timings in order to maintain balance while following a target walking velocity. Our experiments show qualitative and statistical evidence of one of the strongest push-recovery capabilities among humanoid robots to date.

Research of Robot Gait Based on Evolution Algorithms

2011 ◽  
Vol 48-49 ◽  
pp. 928-931 ◽  
Author(s):  
Song Hao Piao ◽  
Xian Feng Wang ◽  
Wen Zhao ◽  
Qiu Bo Zhong
Keyword(s):  
Genetic Algorithm ◽  
Ankle Joint ◽  
Hip Joint ◽  
Humanoid Robot ◽  
Center Of Mass ◽  
Inverted Pendulum Model ◽  
Robot Trajectory ◽  
Pendulum Model ◽  
Link Model ◽  
Evolution Algorithms

In this paper, a new gait research for humanoid robot is presented. By computing the trajectory of center of mass (CoM) for humanoid robot, trajectory of hip joint and ankle joint are developed based on 3D inverted pendulum model. The actual location of the waist position obtained by multi-link model through the center of mass for humanoid robot is in coordinate of the waist of humanoid robot. Trajectory of hip joint and ankle joint are calculated. This paper presents a gait generation method with curve fitting. Using genetic algorithm, humanoid robot can autonomously search for a good gait trajectory. The experimental results show that gait trajectory for humanoid robot can be generated by applying to genetic algorithm. Our proposed method is verified satisfactorily.

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