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To explore the role of the mechanical system in control, we designed a two dimensional, feed–forward, dynamic model of a hexapedal runner (death–head cockroach, Blaberus discoidalis ). We chose to model many–legged, sprawled posture animals because of their remarkable stability. Since sprawled posture animals operate more in the horizontal plane than animals with upright postures, we decoupled the vertical and horizontal plane and only modelled the horizontal plane. The model was feed–forward with no equivalent of neural feedback among any of the components. The model was stable and its forward, lateral and rotational velocities were similar to that measured in the animal at its preferred velocity. It also self–stabilized to velocity perturbations. The rate of recovery depended on the type of perturbation. Recovery from rotational velocity perturbations occurred within one step, whereas recovery from lateral perturbations took multiple strides. Recovery from fore–aft velocity perturbations was the slowest. Perturbations were dynamically coupled—alterations in one velocity component necessarily perturbed the others. Perturbations altered the translation and/or rotation of the body which consequently provided ‘mechanical feedback’ by altering leg moment arms. Self–stabilization by the mechanical system can assist in making the neural contribution of control
Kubow et al. (Sat,) studied this question.