Analysis of gaits for a rotating tripedal robot

Abstract

IntroductionOne of the most striking capabilities of animals in general is their ability to orient to a potential danger and to evade it at high speed if necessary. The erratic zig-zag of a surprised vole, or the almost instantaneous disappearance of a fish when a pebble hits the water, leaves a strong impression of speed and maneuverability. The blend of perception and locomotion abilities required to do this is not something that can be easily reproduced with current robotic technology. The rotopod mechanism [6,7] consists of three legs arranged in a tripod fashion. Each leg has a single translational degree of freedom. A single rotating joint is mounted at the apex of the legs, rotating parallel to the ground plane. The joint continuously rotates a reaction mass mounted at the end of a lever (see Fig. 1). By retracting the legs in turn, the rotating reaction mass can be used to swing the platform around each of the retracted legs. This robot has the advantage of legged locomotion in stepping its 1-DOF legs over objects, but its drive mechanism is a rotating reaction mass that rotates the robot, in a controllable fashion, around each of its legs, similar to a rotating wheel. The mechanism has the potential to transfer the energy from the rotating reaction mass in an efficient manner to the legs, effecting a spinning forward motion. Such a device could have applications as a small fast-moving and extremely agile mobile sensor platform. A large quantity of small versions of this mechanism could be dropped to map and explore an area, or larger versions could be used as for unmanned forward reconnaissance.In [6] we have described the rotopod mechanism and how it can be moved purposefully. [7] builds on this to look at a selection of gaits for the mechanism and introduces a simple power model. In this paper, after a brief review of the mechanism and the method of stepping, we present a taxonomy of gaits for the rotopod, and outline an approach to trajectory generation that takes advantage of the strengths of the unique platform. We conclude with some simulation results for trajectory generation.