8 accepted papers
Real-world applications of path planning must contend with complicated constraint and objective functions imposed by the surrounding operational and regulatory environment. Traditional methods such as PRM* and RRT* have asymptotic guarantees, but often struggle in practice with complex blackbox obje
We propose multi-horizon Monte Carlo tree search (MH-MCTS), the first framework for integrated hierarchical multi-horizon, multi-agent planning based on Monte Carlo tree search (MCTS). The method employs multiple simultaneous MCTS optimisations for each planning level within each agent, which are de
Improving the safety and efficiency of maritime shipping has the potential to reduce carbon emissions and improve profitability. Stochastic ship routing, the problem of finding a safe, efficient, and timely route for a ship is difficult in large part because of uncertainty in weather forecasts, whic…
Climbing robots have the potential to revolutionize the maintenance and inspection operations of many types of vertical structures. In nature, parrots exhibit a remarkable capacity for manipulation during climbing behaviors, for which robotics can benefit from studying. In this paper we present a no…
Estimating ocean flow fields in 3D is a critical step in enabling the reliable operation of underwater gliders and other small, low-powered autonomous marine vehicles. Existing methods produce depth-averaged 2D layers arranged at discrete vertical intervals, but this type of estimation can lead to s…
We present a method to estimate two-dimensional, time-invariant oceanic flow fields based on data from both ensemble forecasts and online measurements. Our method produces a realistic estimate in a computationally efficient manner suitable for use in marine robotics for path planning and related app…
In this letter, we show that for a minimal 2D pose-graph SLAM problem, even in the ideal case of perfect measurements and spherical covariance, using geodesic distance (in 2D, the “wrap function”) to compare angles results in multiple suboptimal local minima. We numerically estimate regions of attra
Dynamic walking robots have the potential for efficient and lifelike locomotion, but computing efficient gaits and tracking them is difficult in the presence of under-modeling. Iterative Learning Control (ILC) is a method to learn the control signal to track a periodic reference over several attempt…