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Autonomous control of mobile robots is a research topic that has received a lot of interest. There are several challenging problems associated with autonomous mobile robots, including low-level control, localisation, and navigation. Most research in the past has focused on developing algorithms for three or four-wheeled mobile robots, such as autonomous cars and differential drive robots, which are statically stable systems. In this thesis, autonomous two-wheeled robots are considered, such as autonomous bicycles, which are naturally unstable systems, and without proper actuation, they will lose balance and fall over. Thus, before developing algorithms for higher-level functionality such as localisation and navigation of an autonomous bicycle, the balance of the bicycle needs to be addressed. This is an interesting research problem as the bicycle is a statically unstable system that has proven difficult to control, but given adequate forward velocity, it is possible to balance a bicycle using only steering actuation. Moreover, given a sufficient forward velocity, the bicycle can even become self-stabilised.

In this thesis, the balance and trajectory tracking of an autonomous bicycle is investigated. First, we propose an extension of previously proposed bicycle models to capture the steering dynamics including the motor used for controlling the handlebar. Next, several control methods which can stabilise an autonomous bicycle by actuation of the steering axis and the forward velocity of the bicycle are developed. The controllers are compared in simulations on both a linear and nonlinear bicycle model. The simulation evaluation proceeds with experiments conducted on an instrumented bicycle running on a bicycle roller. Moreover, trajectory tracking of an autonomous bicycle is addressed using a model predictive controller approach where the reference lean angle is computed at every sample interval and is tracked by the balance controller in the inner loop. Finally, path planning in a static environment is considered where the proposed strategy realises a smooth path that adheres to the kinematic and dynamic constraints of the bicycle while avoiding obstacles and optimises the number of heading changes and the path distance. The results obtained from detailed multibody simulations highlight the feasibility of the balance controller, trajectory tracking controller, and path planner.