An effective trajectory generation method for bipedal walking

Ha, Tae‐Youl; Choi, Chong‐Ho

doi:10.1016/j.robot.2007.06.001

Cited by 43 publications

(44 citation statements)

References 38 publications

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“…The VHIPM is derived under the assumptions that the position variation of each link in the z-direction is small and smooth, and each link position in the x-(y-) direction is approximately linear to ( ) , β the ZMP trajectory error varies greatly for a given COG trajectory. By setting α and β appropriately, it has been found that the ZMP trajectory error could be reduced significantly [14]. It is noted that the COG trajectory, generated by VHIPM, is the same as that by IPM when α = β =1.…”

Section: Desired Trajectory Generation For Walking Upstairs and Accmentioning

confidence: 96%

“…On the other hand, MMIPM is more accurate, but is difficult to use in real time because it requires a long computational processing time. The VHIPM [14,15], based on the IPM, is simple and can significantly reduce the ZMP error by adjusting the height of the inverted pendulum (see (7)). In order to maximize the ZMP margin, the desired ZMP trajectory is set at the middle of the supporting leg.…”

Section: Desired Trajectory Generation For Walking Upstairs and Accmentioning

confidence: 99%

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Trajectory generation and control for a biped robot walking upstairs

Park

Kim

et al. 2010

Int. J. Control Autom. Syst.

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This paper presents an effective and systematic trajectory generation method, together with a control method for enabling a biped robot to walk upstairs. The COG (center of gravity) trajectory is generated by the VHIPM (virtual height inverted pendulum mode) for the horizontal motion and by a 6th order polynomial for the vertical motion; an ankle compliance control (ACC) is also added into the robot control. The proposed methods are evaluated by simulations as well as being implemented in a robot for the performance verification. The results show that the proposed methods can generate stable motions when walking upstairs, and these can significantly reduce the zero moment point (ZMP) errors compared with other methods, enabling the robot to walk up steeper stairs.

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Section: Desired Trajectory Generation For Walking Upstairs and Accmentioning

confidence: 96%

Section: Desired Trajectory Generation For Walking Upstairs and Accmentioning

confidence: 99%

Trajectory generation and control for a biped robot walking upstairs

Park

Kim

et al. 2010

Int. J. Control Autom. Syst.

Self Cite

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“…In order to simplify the association of features, the height of hip in terms of f l−thigh and f r−thigh is fixed, which is a reasonable approximation as long as the human is standing or walking only [11]. Furthermore the links 2,3,8 and 9 are approximated to have only one DOF, as we ignore the vertical rotation of the torso and hip.…”

Section: Human Modeling and Data Associationmentioning

confidence: 99%

Real-time human body motion estimation based on multi-layer laser scans

Wang

Brščić

Hirche

et al. 2011

2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

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-Real time human body motion estimation plays an important role in the perception for robotics nowadays, especially for the applications of human robot interaction and service robotics. In this paper, we propose a method for real-time 3D human body motion estimation based on 3-layer laser scans. All the useful scanned points, presenting the human body contour information, are subtracted from the learned background of the environment. For human contour feature extraction, in order to avoid the situations of unsuccessful segmentation, we propose a novel iterative template matching algorithm for clustering, where the templates of torso and hip sections are modeled with different radii. Robust distinct human motion features are extracted using maximum likelihood estimation and nearest neighbor clustering method. Subsequently, the positions of human joints in 3D space are retrieved by associating the extracted features with a pre-defined articulated model of human body. Finally we demonstrate our proposed methods through experiments, which show accurate human body motion tracking in real time.

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“…Yet, as LIPM model does not count for full body dynamics, this causes ZMP errors, which in turn may become critical for a particular walking speed. To deal with this issue, Ha and Cho 9 proposed a novel simplified robot model, which is called Virtual Height Inverted Pendulum Model (VHIPM) and experimentally demonstrated that the ZMP error could be significantly reduced by varying the height of Center of Mass (CoM) in their LIPM model. In this paper we present two pattern generation principles: preview control method and VHIPM method with LIPM model 10,11 .…”

Section: Introductionmentioning

confidence: 99%

Bipedal robot locomotion modelling with virtual height inverted pendulum and preview control approaches in Simulink environment

Khusainov¹,

Afanasyev²,

Sabirova³

et al. 2016

JRNAL

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Control algorithms development for humanoid locomotion is difficult due to humanoid's high number of Degrees of Freedom and system nonlinearity. Moreover, a humanoid may lose balance as its walking speed changes. We present AR-601M humanoid locomotion modelling with virtual height inverted pendulum and preview control approaches. A step length and period influence on walking stability were investigated and simulated within Simulink environment. Achievable in simulation maximal torques in leg joints and corresponding trajectories were verified against attainable robot motors' values.

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An effective trajectory generation method for bipedal walking

Cited by 43 publications

References 38 publications

Trajectory generation and control for a biped robot walking upstairs

Trajectory generation and control for a biped robot walking upstairs

Real-time human body motion estimation based on multi-layer laser scans

Bipedal robot locomotion modelling with virtual height inverted pendulum and preview control approaches in Simulink environment

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