Center of percussion and gait design of biped robots

Alba, Mauricio; García-Prada, Juan Carlos; Meneses, J.; Rubio, Higinio

doi:10.1016/j.mechmachtheory.2010.06.008

Cited by 21 publications

(17 citation statements)

References 6 publications

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“…Therefore, the impulse at the heel contact is not considered in formulating the dynamics. The SS phase analysis is identified in this research because the passivity and dynamicity in the double support (DS) phase are not as important as in the SS phase due to its relatively short duration 37 and less dynamic nature -usually both GCOM and ZMP exist within the FSR; 20 this is also consistent with many SS phase models described earlier. 37 For simplicity, a two-dimensional (2D) planar biped system is modeled where the motion is confined in the sagittal plane ( Fig.…”

Section: Biped System Model and Dynamicssupporting

confidence: 65%

“…The SS phase analysis is identified in this research because the passivity and dynamicity in the double support (DS) phase are not as important as in the SS phase due to its relatively short duration 37 and less dynamic nature -usually both GCOM and ZMP exist within the FSR; 20 this is also consistent with many SS phase models described earlier. Therefore, the impulse at the heel contact is not considered in formulating the dynamics.…”

Section: Biped System Model and Dynamicssupporting

confidence: 65%

“…37 In the sagittal plane, foot dimensions are foot height fh and foot length a + b (Fig. 37 In the sagittal plane, foot dimensions are foot height fh and foot length a + b (Fig.…”

Section: Gait Modelingmentioning

confidence: 99%

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Passive and dynamic gait measures for biped mechanism: formulation and simulation analysis

Mummolo

Kim

2012

Robotica

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Understanding and mimicking human gait is essential for design and control of biped walking robots. The unique characteristics of normal human gait are described as passive dynamic walking, whereas general human gait is neither completely passive nor always dynamic. To study various walking motions, it is important to quantify the different levels of passivity and dynamicity, which have not been addressed in the current literature. In this paper, we introduce the initial formulations of Passive Gait Measure (PGM) and Dynamic Gait Measure (DGM) that quantify passivity and dynamicity, respectively, of a given biped walking motion, and the proposed formulations will be demonstrated for proof-of-concepts using gait simulation and analysis. The PGM is associated with the optimality of natural human walking, where the passivity weight functions are proposed and incorporated in the minimization of physiologically inspired weighted actuator torques. The PGM then measures the relative contribution of the stance ankle actuation. The DGM is associated with the gait stability, and quantifies the effects of inertia in terms of the Zero-Moment Point and the ground projection of center of mass. In addition, the DGM takes into account the stance foot dimension and the relative threshold between static and dynamic walking. As examples, both human-like and robotic walking motions during single support phase are generated for a planar biped system using the passivity weights and proper gait parameters. The calculated PGM values show more passive nature of human-like walking as compared with the robotic walking. The DGM results verify the dynamic nature of normal human walking with anthropomorphic foot dimension. In general, the DGMs for human-like walking are greater than those for robotic walking. The resulting DGMs also demonstrate their dependence on the stance foot dimension as well as the walking motion; for a given walking motion, smaller foot dimension results in increased dynamicity. Future work on experimental validation and demonstration will involve actual walking robots and human subjects. The proposed results will benefit the human gait studies and the development of walking robots.

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Section: Biped System Model and Dynamicssupporting

confidence: 65%

Section: Biped System Model and Dynamicssupporting

confidence: 65%

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Passive and dynamic gait measures for biped mechanism: formulation and simulation analysis

Mummolo

Kim

2012

Robotica

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“…As an example of the latter, the external forces and inertias acting on passive and quasi-passive bipeds are manipulated to minimize the power loss [8] [9].…”

Section: Introductionmentioning

confidence: 99%

Forward and Inverse Dynamics of the Biped PASIBOT

Corral

Meneses

Castejón

et al. 2014

International Journal of Advanced Robotic Systems

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This article addresses the supporting foot slippage of the biped robot PASIBOT and develops its forward and inverse dynamics for simple and double support phases. To address the slippage phenomenon, we consider an additional degree of freedom at the supporting foot and also distinguish between static and kinetic friction conditions. The inverse and forward dynamics, accounting for support foot slippage, are encoded in MATLAB. The algorithm predicts the motion of the biped from the torque function given by the biped's sole motor. Thus, the algorithm becomes an indispensable tool for studying transient states of the biped (for example, the torques required for starting and braking), as well as defining the conditions that prevent or control slippage. Since the developed code is parametric, its output can greatly assist in the design, optimization and control of PASIBOT and similar biped robots. The topology, kinematics and inverse dynamics of the one-degree-of-freedom biped PASIBOT have been previously described, but without regard to slippage between the supporting foot and the ground.

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“…A unified feedback control law for n degree of freedom biped robots with one degree of under actuation has been developed by Hu et al [4] so as to generate periodic orbits on different slopes. Alba et al [5] proposed a novel gait generation technique to optimize the mechanical design of actuated bipeds in order to reduce energy consumption. The centre of percussion of the robot is used to calculate the equivalent simple pendulum of the system and control is achieved by designing an adaptive PD controller for gait generation.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Velocity Control of a Biped Robot Locomotion and Simulation

Ankarali

2012

International Journal of Advanced Robotic Systems

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In this paper, fuzzy logic velocity control of a biped robot to generate gait is studied. The system considered in this study has six degrees of freedom with hip, knee and ankle joints. The joint angular positions are determined utilizing the Cartesian coordinate information of the joints obtained by using camera captured data of the motion. The first derivatives of the calculated joint angular positions are applied as the reference angular velocity input to the fuzzy controllers of the joint servomotors to generate a gait motion. The assumed motion for the biped robot is horizontal walking on a flat surface. The actuated joints are hip, knee and ankle joints which are driven by DC servomotors. The calculated angular velocities of the joints from camera captured motion data are utilized to get the driving velocity functions of the model as sine functions. These functions are applied to the fuzzy controller as the reference angular velocity inputs. The control signals produced by the fuzzy controllers are applied to the servomotors and then the response of the servomotor block is introduced as an input to the SimMechanics model of the biped robot. The simulation results are provided which evaluate the effectiveness of the fuzzy logic controller on joint velocities to generate gait motion.

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Center of percussion and gait design of biped robots

Cited by 21 publications

References 6 publications

Passive and dynamic gait measures for biped mechanism: formulation and simulation analysis

Passive and dynamic gait measures for biped mechanism: formulation and simulation analysis

Forward and Inverse Dynamics of the Biped PASIBOT

Fuzzy Logic Velocity Control of a Biped Robot Locomotion and Simulation

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