A simple rule for quadrupedal gait generation determined by leg loading feedback: a modeling study

Abstract

We discovered a specific rule for generating typical quadrupedal gaits (the order of the movement of four legs) through a simulated quadrupedal locomotion, in which unprogrammed gaits (diagonal/lateral sequence walks, left/right-lead canters, and left/right-lead transverse gallops) spontaneously emerged because of leg loading feedbacks to the CPGs hard-wired to produce a default trot. Additionally, all gaits transitioned according to speed, as seen in animals. We have therefore hypothesized that various gaits derive from a trot because of posture control through leg loading feedback. The body tilt on the two support legs of each diagonal pair during trotting was classified into three types (level, tilted up, or tilted down) according to speed. The load difference between the two legs led to the phase difference between their CPGs via the loading feedbacks, resulting in nine gaits (32: three tilts to the power of two diagonal pairs) including the aforementioned.

Realizing Learned Quadruped Locomotion Behaviors through Kinematic Motion Primitives

“…Quadrupedal animals typically have eight types of gaits [32], [33]. Reference trajectories were used in [11] open-loop signals were used in [10] to learn a specific gait.…”

The Analysis of Mechanical Structure of a Robotic Leg in Running for Impact Mitigation

“…Applying (13) and (15), λ 2 can be calculated depending on r as shown in Figure 4. As COM drifts away from the point of contact, CI decreases.…”

“…The locomotion of legged animals is typically divided into two phases: stance and swing. When they run, another version of the swing phase, i.e., no feet in contact with the ground, rises contrary to the original version of the swing phase, i.e., at least one foot on the ground, which is observed during walking [13][14][15]. At the end of the swing phase, a foot or feet touch(es) the ground.…”

Gait Generation and Its Energy Efficiency Based on Rat Neuromusculoskeletal Model

“…It is difficult to fully analyze the locomotor mechanism with animal data alone. Recently, modeling studies have attracted attention because physiological findings and hypotheses can be used to develop reasonably realistic motor control models, and biomechanical and anatomical findings can be used to construct detailed musculoskeletal models (Ivashko et al, 2003;Yakovenko et al, 2004;Ekeberg and Pearson, 2005;Nishii, 2006;Aoi et al, 2013a;Fukuoka et al, 2015;Hunt et al, 2015;Aoi and Funato, 2016;Markin et al, 2016;Fujiki et al, 2018). Motor control and musculoskeletal models are integrated to produce locomotion through forward dynamics simulation.…”