Modern robots are increasingly capable of performing “basic” activities such as localization,
navigation, and motion planning. However, for a robot to be considered intelligent, we would …

Many planning applications involve complex relationships defined on high-dimensional,
continuous variables. For example, robotic manipulation requires planning with kinematic …

We generalise the interval-based relaxation to sequential numeric planning problems with
non-linear conditions and effects, and cyclic dependencies. This effectively removes all the …

Powerful domain-independent planners have been developed to solve various types of
planning problems. These planners often require a model of the acting agent's actions …

In order to engender trust in AI, humans must understand what an AI system is trying to
achieve, and why. To overcome this problem, the underlying AI process must produce …

The automatic generation of realistic behaviour such as tactical intercepts for Unmanned
Aerial Vehicles (UAV) in air combat is a challenging problem. State-of-the-art solutions …

The state of the art practice in robotics planning is to script behaviors manually, where each
behavior is typically generated using trajectory optimization. However, in order for robots to …

Real-world applications of AI Planning often require a highly expressive modeling language
to accurately capture important intricacies of target systems. Hybrid systems are ubiquitous …

This paper discusses the issue of efficient resolution of timeline-based planning problems. In
particular, taking inspiration from the more classical heuristics for the resolution of STRIPS …

Mission planning constitutes an important feature of autonomy for Maritime Autonomous
Surface Ships (MASS). Nevertheless, this research topic remains largely unexplored, as the …