The growing variety and complexity of marine research and application oriented tasks
requires unmanned surface vehicles (USVs) to operate fully autonomously over long time …

We introduce a model-predictive trajectory planning algorithm for unmanned surface
vehicles (USVs) operating in congested civilian traffic. The planner reasons about the …

As vehicle automation advances, motion planning algorithms face escalating challenges in
achieving safe and efficient navigation. Existing Advanced Driver Assistance Systems …

Safe and efficient following of a time varying motion goal by an autonomous unmanned
surface vehicle (USV) in a sea environment with obstacles is a challenge. The vehicle's …

We present a model-predictive trajectory planning algorithm for following a target boat by an
autonomous unmanned surface vehicle (USV) in an environment with static obstacle …

The task of maneuvering ships in confined environments is a difficult task for a human
operator. One major reason is due to the complex and slow dynamics of the ship which need …

Motion planning in off-road environments re-quires reasoning about both the geometry and
semantics of the scene (eg, a robot may be able to drive through soft bushes but not a fallen …

Motion planning algorithms for urban automated driving must handle uncertainty due to
unknown intention and future motion of Dynamic Obstacles (DOs). Considering a single …

Optimization-based methods are commonly applied in autonomous driving trajectory
planners, which transform the continuous-time trajectory planning problem into a finite …

Motion planning for autonomous surface vehicles (ASVs) is challenging since surface
vessels are nonlinear underactuated kinodynamic systems with often large inertia. Thus …