PubMed · 14048115
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E J CARLIN. 1963. HUMAN GAIT.. https://pubmed.ncbi.nlm.nih.gov/14048115/
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Stability is a key element in a gait synthesis. Static stability margins are widely adopted in crawlers, while no similar approach has been developed for dynamically stable systems. Utilizing an analytical approach, we developed a set of easy-to-calculate stability indices to describe instantaneous static and dynamic (In)stability for a certain group of walking systems. The analysis is based on a thorough analysis of the interaction between ground reaction forces and the walking system. The indices are applicable to walking systems regardless of the number of legs or mechanical/biological design. We show that static and dynamic stability are independent of each other. We suggest a possible categorization of gait modes based on stability. Stability characteristics are analyzed in a healthy and highly pathological human gait. Finally, we discuss the applicability of the proposed methods.
Based on mechanical analysis, three gait descriptors are found which should be controlled to generate cyclic gait of a seven-link humanoid biped in the sagittal plane: (i) step length, (ii) step time, and (iii) the velocity of the center of mass (CoM) at push off. Two of these three gait descriptors can be chosen independently, since the CoM moves almost ballistically during the swing phase. These gait descriptors are formulated as end-point conditions and are regulated by a model predictive controller. In addition, continuous controls at the trunk and knees are implemented to maintain the trunk upright and to ensure weight bearing. The model predictive controller is realized by quadratic dynamic matrix control, which offers the possibility of including constraints that are exposed by the environment and the biped itself. Specifying step length and CoM velocity at push off, the controller generates a symmetric and stable gait. The proposed control scheme serves as a general-purpose solution for the generation of a bipedal gait. The proposed model contains fewer parameters than other models, and they are all directly related to determinants of bipedal gait: step length, trunk orientation, step time, walking velocity, and weight bearing. The proposed control objectives and the model of humanoid bipedal walking have potential applications in robotics and rehabilitation engineering.
The concerted and self-organizing behavior of spinal cord segments in generating locomotor patterns is modulated by afferent sensory information and controlled by descending pathways from the brainstem, cerebellum, or cortex. The purpose of this study was to define a minimal set of parameters that could control a similar self-organizing behavior in a two-dimensional neural network. When we implemented synaptic depression and active membrane repolarization as two properties of the neurons, the two-dimensional neural network generated traveling waves. Their wavelength and angle of propagation could be independently controlled by two parameters that modulated excitatory premotor neurons and inhibitory commissural neurons. It is further demonstrated that the selection of wave parameters corresponds to the selection of quadruped gaits.