5 accepted papers
This paper considers planning missions for a fleet of robots with limited energy. Each robot has size, heading, and velocity and its motion is described by non-linear differential equations. The dynamics of movements, existing obstacles, multiple robots, and waypoints are additional challenges, as t…
In imitation learning for planning, parameters of heuristic functions are optimized against a set of solved problem instances. This work revisits the necessary and sufficient conditions of strictly optimally efficient heuristics for forward search algorithms, mainly A* and greedy best-first search,…
Effective decision making while competing for limited resources in adversarial environments is important for many real-world applications (e.g. two Taxi companies competing for customers). Decision-making techniques such as Automated planning have to take into account possible actions of adversary (…
Robots used for inspection, package deliveries, moving of goods, and other logistics operations are often required to visit certain locations within specified time bounds. This gives rise to a challenging problem as it requires not only planning collision-free and dynamically feasible motions but al
This paper develops an efficient approach to generate a collision-free and dynamically feasible trajectory that enables a robotic vehicle to inspect the entire workspace or a subset consisting of one or several regions. The approach makes it possible to specify constraints on the order in which the