Kinematical modeling and optimal design of a biped robot joint parallel linkage

AUTOR(ES)

Menegaldo, Luciano L., Santana, Rogerio Eduardo S., Fleury, Agenor de Toledo

FONTE

Journal of the Brazilian Society of Mechanical Sciences and Engineering

DATA DE PUBLICAÇÃO

2006-12

RESUMO

This paper shows the design and analysis of a parallel three-dimensional linkage, conceived to work as the ankle and hip joints of an anthropometric biped robot. This kind of mechanism architecture provides low-weight, highly stable assemblies, and allows the use of actuator synergies. On the other hand, the mechanical transmission ratio is not usually favorable, and a non-linear kinematic model has to be derived and solved. The mechanism proposed here is driven by two rotational servo-actuators, and allows the joint to follow a specified angular trajectory determined by the gait pattern. Namely, the joint linkage can generate dorsi/plantar flexion and inversion/eversion of the ankle, and hip flexion/extension and adduction/abduction movements. Several approaches to the direct and inverse kinematical modeling of the linkage are presented and compared, regarding their accuracy and computational cost, where the last performance parameter is closely related to on-line computer implementing of the controller. Strategies to fit current gait angular amplitudes into the linkage workspace, as well as singularity analysis, are discussed. An optimization method was applied to find some geometrical design parameters of the linkage that minimizes a cost function. This function is the mean transmission ratio between the motor inputs and the joint output torques over a predefined dominion. The minimization is constrained to a minimum workspace area value and to minimum and maximum values of the design parameters. Several design solutions were generated. The chosen was one where the workspace is compatible to the gait amplitude requirements and that exhibits the lowest cost function. A biped robot using the linkage geometry designed in this paper has been built and tested with real human gait data acquired in a gait lab.

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