Nowadays, the state of the art in robotics reached a point when troops in military operations theatre routinely deploy unmanned robotic assets, be it unmanned aerial and ground vehicles, or unattended ground sensors supporting them in carrying out their tactical missions. Tele-operation of large numbers of such assets drastically raises costs of such operations in terms of costly and scarce expert human resources.
Agile Tactical Operations aim at development and evaluation of multi-agent coordination techniques supporting information-collection missions in tactical urban warfare. The core objective of the cluster is development and evaluation of techniques allowing deployment of teams of autonomous assets which are capable of autonomous coordination and teamwork with the goal to carry out the high-level mission assigned to the team. In particular, we are developing agent-based coordination, planning and game-theoretic techniques for heterogeneous multi-agent teams allowing them to carry out various information collection tasks, such as reconnaissance, convoy and perimeter protection, pursuit-evasion of smart targets, surveillance, safe area traversal, etc.
This topic agregates research achievements mainly from Multi-agent planning and resource allocation and Computational game theory / adversarial reasoning topics and apply them in the complex tactical environment simulation. The goal is to enabling development and validation of AI planning and coordination techniques (not only) for agents coordination in environment of tactical missions using flexible, highly scalable multi-agent simulation of tactical theatre, state-of-the-art planning and coordination techniques and validation and evaluation with high degree of abstraction freedom towards HW deployment.
Main types of addressed tactical misions is so called ISTAR (intelligence, surveillance, target acquisition and recoinnaissance), field support systems, disaster relief scenarios and logistics.
AI research results implemented for tactical missions contains advances of trajectory, path and motion planning of simmulated robotic assets, task and resource allocation, multi-agent planning and coordination, and application of game theory. Selected examples of application are: