  The topological obstructions on the attitude space of a rigid body make
global asymptotic stabilization impossible using continuous state-feedback.
This paper presents novel algorithms to overcome such topological limitations
and achieve arbitrary attitude maneuvers with only continuous, memory-less
state-feedback. We first present nonlinear control laws using both rotation
matrices and quaternions that give rise to one almost globally asymptotically
stabilizable equilibrium along with a nowhere dense set of unstable equilibria.
The unstable equilibria are uniquely identified in the attitude error space.
Pseudo-targets are then designed to make the controller believe that the
attitude error is within the region of attraction of the stable equilibrium.
Further, the pseudo-target ensures that maximum control action is provided to
push the closed-loop system toward the stable equilibrium. The proposed
algorithms are validated using both numerical simulations and experiments to
show their simplicity and effectiveness.
