  This paper presents a novel autonomous surface vessel (ASV), called Roboat II
for urban transportation. Roboat II is capable of accurate simultaneous
localization and mapping (SLAM), receding horizon tracking control and
estimation, and path planning. Roboat II is designed to maximize the internal
space for transport and can carry payloads several times of its own weight.
Moreover, it is capable of holonomic motions to facilitate transporting,
docking, and inter-connectivity between boats. The proposed SLAM system
receives sensor data from a 3D LiDAR, an IMU, and a GPS, and utilizes a factor
graph to tackle the multi-sensor fusion problem. To cope with the complex
dynamics in the water, Roboat II employs an online nonlinear model predictive
controller (NMPC), where we experimentally estimated the dynamical model of the
vessel in order to achieve superior performance for tracking control. The
states of Roboat II are simultaneously estimated using a nonlinear moving
horizon estimation (NMHE) algorithm. Experiments demonstrate that Roboat II is
able to successfully perform online mapping and localization, plan its path and
robustly track the planned trajectory in the confined river, implying that this
autonomous vessel holds the promise on potential applications in transporting
humans and goods in many of the waterways nowadays.
