Morphological design for controlled tensegrity quadruped locomotion

From the viewpoint of evolution, vertebrates first accomplished locomotion via motion of the spine. Legs evolved later, to enhance mobility, but the spine remains central. Contrary to this, most robots have rigid torsos and rely primarily on movement of the legs for mobility. The force distributing properties of tensegrity structures presents a potential means of developing compliant spines for legged robots, with the goal of driving motion from the robots core. We present an initial exploration of the morphological design of a tensegrity quadruped robot, the first to the authors' knowledge, which we call MountainGoat, and its impact on controllable locomotion. All parts of the robot, including legs and spine, are compliant. Locomotion is aided by the use of central pattern generators, feedback control via a neural network, and machine learning techniques involving the Monte Carlo method as well as genetic evolution for parameter optimization. Control is demonstrated with three variations of MountainGoat, focusing on actuation of the spine as central to the locomotion process.