State estimation of a cheetah spine and tail using an inertial sensor network

Abstract

The cheetah (Acinonyx jubatus) is by far the most manoeuvrable and agile terrestrial animal. Little is known, in terms of biomechanics, about how it achieves these incredible feats of manoeuvrability. The transient motions of the cheetah all involve rapid flicking of its tail and flexing of its spine. The aim of the research was to develop tools (hardware and software) that can be used to gain a better understanding of the cheetah tail and spine by capturing its motion. A mechanical rig was used to simulate the tail and spine motion. This insight may inspire and aid in the design of bio-inspired robotic platforms. A previous assumption was that the tail is heavy and acts as a counter balance or rudder, yet this was never tested. Contrary to this assumption, necropsy results determined that the tail was in fact light with a relatively low inertia value. Fur from the tail was used in wind tunnel experiments to determine the drag coefficient of a cheetah tail. No researchers have actively sought to track the motion of a cheetah's spine and tail during rapid manoeuvres via placing multiple sensors on a cheetah. This requires the development of a 3D dynamic model of the spine and tail to accurately study the motion of the cheetah. A wireless sensor network was built and three different filters and state estimation algorithms were designed and validated with a mechanical rig and camera system. The sensor network consists of three sensors on the tail (base, middle and tip) as well as a hypothetical collar sensor (GPS and WiFi were not implemented).