On Game-Theoretic Planning with Unknown Opponents' Objectives

Many autonomous navigation tasks require mobile robots to operate in dynamic environments involving interactions between agents. Developing interaction-aware motion planning algorithms that enable safe and intelligent interactions remains challenging. Dynamic game theory renders a powerful mathematical framework to model these interactions...

Knowledge-based Approach for Mobile Manipulation with Active Inference

Achieving human-like action planning requires profound reasoning and context-awareness capabilities. It is especially true for autonomous robotic mobile manipulation in dynamic environments. In the case of component failure, the autonomous robotic system requires reliable adaptation capabilities combined with a consistent understanding of the...

Multi-­Robot Exploration and Planning in Limited Communication Environments

Distributed cooperative robots can be highly beneficial in mapping disaster environments and assisting with search and rescue operations. In most situations such environments only allow for only limited communication between robots. This thesis reports on simulation experiments conducted to test the impact of having only partial communication...