Limit cycle based walk of a powered 7DOF 3D biped with flat feet

Harada, Yuzuru; Takahashi, Jun; Nenchev, Dragomir N.; Sato, Daisuke

doi:10.1109/iros.2010.5651546

Cited by 14 publications

(5 citation statements)

References 22 publications

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“…However, the walking profile of the ZMPbased strategy looks waist-lowered, similar to the walking style of monkeys. As alternatives to the ZMP, other approaches have focused on keeping the robot's walking trajectories inside a basin of attraction [3][4][5], including a method that refers to the limit cycle in order to determine the input torque [6].…”

Section: Introductionmentioning

confidence: 99%

Visual Lifting Approach for Bipedal Walking with Slippage

Minami²,

Matsuno³

et al. 2017

J. Robot. Mechatron.

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[abstFig src='/00290003/05.jpg' width='300' text='Concept of visual lifting approach' ] Biped locomotion generated by control methods based on Zero-Moment Point (ZMP) has been achieved and its efficacy for stable walking, where ZMP-based walking does not include the falling state, has been verified extensively. The walking control that does not depend on ZMP – we call it dynamical walking – can be used in walking that utilizes kicks by toes, which looks natural but is vulnerable to turnover. Therefore, keeping the walking of dynamical motion stable is indispensable to the realization of human-like natural walking – the authors perceive the human walking, which includes toe off states, as natural walking. Our research group has developed a walking model, which includes slipping, impact, surface-contacting and line-contacting of foot. This model was derived from the Newton-Euler (NE) method. The “Visual Lifting Approach” (VLA) strategy inspired from human walking motion utilizing visual perception, was used in order to enhance robust walking and prevent the robot from falling, without utilizing ZMP. The VLA consists of walking gate generation visual lifting feedback and feedforward. In this study, simulation results confirmed that bipedal walking dynamics, which include a slipping state between foot and floor, converge to a stable walking limit cycle.

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Section: Introductionmentioning

confidence: 99%

Visual Lifting Approach for Bipedal Walking with Slippage

Minami²,

Matsuno³

et al. 2017

J. Robot. Mechatron.

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“…As for walking control of the humanoid, ZMPbased walking is known as the most potential approach, which has been proved to be a realistic control strategy to demonstrate stable walking of actual biped robots, since it can guarantee that the robots can keep standing by retaining the ZMP within the convex hull of supporting area [6], [7]. Instead of the ZMP, there are another approaches that put the importance on keeping the robot's walking trajectories inside of a basin of attraction [8], [9] including a method referring limit cycle to determine input torque [10].…”

Section: Introductionmentioning

confidence: 99%

A first step of humanoid's walking by two degree-of-freedom generalized predictive control combined with Visual Lifting Stabilization

Yanou

Minami

Maeba

et al. 2013

IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society

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Biped locomotion created by a controller based on Zero-Moment Point (ZMP) known as reliable control method looks different from human's walking on the view point that ZMP-based walking does not include falling state. However, the walking control that does not depend on ZMP is vulnerable to turnover. Therefore, keeping the walking of dynamical motion stable is inevitable issue for realization of human-like natural walking-we call the humans' walking that includes turning over states as "natural." In our research group, walking model including slipping, impact, surface-contacting and pointcontacting of foot has been developed. Although "Visual Lifting Stabilization" (VLS) strategy has been also proposed in order to enhance standing robustness and prevent the robot from falling down without utilizing ZMP, the torque generation strategy making lifted-leg step forward is derived by trial and error. Therefore, as a first step to realize humans' walking, this paper explores two degree-of-freedom generalized predictive control (GPC) method in order to generate the torque making liftedleg step forward. Simulation results indicate that this strategy helps stabilize bipedal walking even though ZMP is not kept inside convex hull of supporting area.

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“…Instead of the ZMP, another approaches that put the importance on keeping the robot's walking trajectories inside of a basin of attraction [12]- [14] including a method referring limit cycle to determine input torque [15].…”

Section: Introductionmentioning

confidence: 99%

Dynamical analyses of humanoid's walking by visual lifting stabilization based on event-driven state transition

Maeba

Minami

Yanou

et al. 2012

2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)

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Biped locomotion created by a controller based on Zero-Moment Point [ZMP] known as reliable control method looks different from human's walking on the view point that ZMP-based walking does not include falling state. However, the walking control that does not depend on ZMP is vulnerable to turnover. Therefore, keeping the event-driven walking of dynamical motion stable is important issue for realization of human-like natural walking. In this paper, walking model of humanoid including slipping, bumping, surface-contacting and point-contacting of foot is discussed, and its dynamical equation is derived by Newton-Euler method. Then, we propose walking stabilizer named "Visual Lifting Stabilization" strategy to enhance standing robustness and prevent the robot from falling down. Simulation results indicate that this strategy helps stabilize pose and bipedal walking even though ZMP is not kept inside convex hull of supporting area.

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Limit cycle based walk of a powered 7DOF 3D biped with flat feet

Cited by 14 publications

References 22 publications

Visual Lifting Approach for Bipedal Walking with Slippage

Visual Lifting Approach for Bipedal Walking with Slippage

A first step of humanoid's walking by two degree-of-freedom generalized predictive control combined with Visual Lifting Stabilization

Dynamical analyses of humanoid's walking by visual lifting stabilization based on event-driven state transition

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