  This paper proposes a robust lattice-based motion-planning algorithm for
nonlinear systems affected by a bounded disturbance. The proposed motion
planner utilizes the nominal disturbance-free system model to generate motion
primitives, which are associated with fixed-size tubes. These tubes are
characterized through designing a feedback controller, that guarantees
boundedness of the errors occurring due to mismatch between the disturbed
nonlinear system and the nominal system. The motion planner then sequentially
implements the tube-based motion primitives while solving an online
graph-search problem. The objective of the graph-search problem is to connect
the initial state to the final state, through sampled states in a suitably
discretized state space, such that the tubes do not pass through any unsafe
states (representing obstacles) appearing during runtime. The proposed strategy
is implemented on an Euler-Lagrange based ship model which is affected by
significant wind disturbance. It is shown that the uncertain system
trajectories always stay within a suitably constructed tube around the nominal
trajectory and terminate within a region around the final state, whose size is
dictated by the size of the tube.
