Visual Lifting stabilization of dynamic Bipedal Walking

Song, Wei; Minami, Mamoru; Maeba, Tomohide; Zhang, Yanan; Yanou, Akira

doi:10.1109/humanoids.2011.6100840

Cited by 7 publications

(5 citation statements)

References 15 publications

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“…Using software simulation, it may fall in meaningless discussions unless the dynamical model describes correctly the real physical dynamical behavior. In line with this thinking way, we have discussed a dynamical model of humanoid's walking motion including slipping, bumping and tipping over [9]. Using correct model, simulations enables us to obtain every piece of data without real sensors and can discuss about phenomenon being hard to obtain from real machine, e.g.…”

Section: Introductionmentioning

confidence: 92%

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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Section: Introductionmentioning

confidence: 92%

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)

Self Cite

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“…In our research group, ZMPindependent walking method has been proposed to realize human-like natural walking including tipping over state, that is a method to enhance standing robustness named "Visual Lifting Stabilization" (VLS) strategy [14] based on visual servoing and visual feedback concept, which is based on a similar concept of impedance control method [15]. But the torque generation strategy making lifted-leg step forward is derived by trial and error.…”

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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“…In the visual lifting approach, we utilize real-time pose tracking method to observe a static object that is set in front of the robot to measure the robot's head position/orientation based on the object through visual pose estimation [24], [25] during walking. The simulation results show that visual feedback helps realize stable bipedal walking that ZMP is not kept within convex hull of supporting area on condition that humanoid's dynamics includes tipping, slipping and bumping [27], [28].…”

Section: Introductionmentioning

confidence: 99%

Walking analyses of a humanoid by visual-lifting approach

et al. 2013

Self Cite

View full text Add to dashboard Cite

Biped locomotion created by a controller based on ZMP known as reliable control method looks different from human's walking on the view point that ZMP-based walking does not include tipping-over state. However, the walking control that does not depend on ZMP is vulnerable to turnover. Therefore, we propose walking stabilizer based on visual feedback to enhance standing robustness and prevent the robot from falling down. Simulation results indicate that this stabilizer helps stabilize pose and bipedal walking even though ZMP is not kept inside convex hull of supporting area. In this report, we discuss proposed visual lifting approach in conjunction wish arms' swinging motion on a viewpoint that the arms' motion helps improve walking efficiency.

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Visual Lifting stabilization of dynamic Bipedal Walking

Cited by 7 publications

References 15 publications

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

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

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

Walking analyses of a humanoid by visual-lifting approach

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