UC Berkeley

Rapid terrestrial locomotion is a fascinating but difficult problem that roboticists face. Considerations must be made towards dynamics, controls, estimation, the environment, electronics, and mechanical design. Wheeled and legged robots have been heavily researched and have gained much success, however they still have their limitations, especially when ground contact is lost.

Inspired by the high performance of lizards actively using their tails to stabilize perturbations and rapidly reorient their body, we propose to add an active inertial appendage to terrestrial robots that will greatly improve their stability and maneuverability.

In this dissertation we present three main focus areas. We first develop the capabilities of a novel tailed robot with an active single degree-of-freedom (DOF) tail. We then discuss the single degree of freedom orientation sensing developed for this robot. Finally, we construct a nonlinear controller to enable reorientation of the body of a 2-link robot in three-dimensions while being constrained to a tail that only has two DOF of actuation.

The first 177 (g) active tailed robot, Tailbot, has a single DOF of actuation and contains attitude inertial sensors. By utilizing both contact forces and zero net angular momentum maneuvering, this tailed robot can rapidly right itself in a fall, avoid flipping over after a large perturbation, and smoothly transition between surfaces of different slopes. We used a modeling approach to show that a tail-like design offers significant advantages to other alternatives, including reaction wheels, when the speed of response is important.

In order to provide the reliable orientation sensing for the single DOF robot we design a novel time varying complementary filter. Complementary filtering (CF) is a signal processing method

that is commonly used for the fusion of gyroscope and accelerometer measurements in order to robustly estimate the attitude of a rigid body. The traditional CF uses linear time invariant filters to combine the two different measurements of the same physical quantity. Here we present an extension to the CF method with time-varying filters. A fuzzy logic method is developed to adjust the parameters. Stability analysis as well as experimental results are presented to verify the proposed

method.

Finally, we propose a nonlinear control scheme for attitude control of a falling, two link active tailed robot with only two DOF of actuation. We derive a simplified expression for the robot's angular momentum and invert this expression to solve for the shape velocities that drive the body's

angular momentum to a desired value. By choosing a body angular velocity vector parallel to the axis of error rotation, the controller steers the robot towards its desired orientation. The proposed scheme is accomplished through feedback laws as opposed to feedforward trajectory generation, is fairly robust to model uncertainties, and is simple enough to implement on a low power microcontroller.

We verify our approach by implementing the controller on a small 175 (g) robot platform, enabling rapid maneuvers approaching the spectacular capability of animals.