Autonomous mobile robots as embodied multi-agent systems: from perception to planning algorithms
PhD
Nicola Basilico, Matteo Luperto
Autonomous mobile robots (AMRs) are embodied agents equipped with sensors and actuators capable of moving and performing tasks in a physical environment. Autonomy, a key feature, refers to the capability of carrying out tasks without direct human supervision. This technology is currently garnering increasing interest in the fields of AI and Robotics. This course aims to provide an introduction to some of the most important and fundamental algorithmic challenges that characterize the field of AMRs. The first part focuses on describing how AMRs perceive and represent their working environments. This knowledge is then used by both single- and multi-agent robotic systems to accomplish assigned tasks. The second part delves into the algorithmic foundations behind the multi-agent planning framework used to formalize and solve these tasks.