This course introduces the core methodologies that underpin robotic systems, focusing on how robots perceive, reason, and act in the physical world. Learners will explore fundamental concepts such as sensing, control, knowledge representation, and manipulation. Participants will develop a structured understanding of the principles enabling intelligent robotic behavior.
This course is part of the "Robotics & Robots" Specialization.
Contributors:
Prof. Bruno Siciliano, University of Naples, Federico II (curator)
Proff. Oussama Khatib, Stanford University; Michael Beetz/Leonie Dziomba, University of Bremen; Fabrizio Caccavale, University of Basilicata; Andreas Nüchter, Julius Maximilian University of Würzburg/Dorit Borrmann, Technical University of Applied Sciences Würzburg-Schweinfurt; Domenico Prattichizzo/Monica Malvezzi/Maria Pozzi, University of Siena; Guglielmo Tamburrini, University of Naples, Federico II; Marilena Vendittelli, Sapienza University of Rome; Luigi Villani, University of Naples, Federico II
"A special mention goes to Mario Selvaggio for his tireless dedication to the project, interacting with all the lesson authors, ensuring consistency and soundness throughout, also in connection with the Springer Nature books supporting the MOOC course. His contribution to defining the problems posed at the end of the various lessons was crucial" - Bruno Siciliano
This week introduces the origins and evolution of robotics, from its early development in the twentieth century to current and future trends. Learners explore the notion of the robot as a physical system, understanding its role as an intersection of mechanics, control, and intelligence. The second…
This week explores how robots perceive their state and environment, and how they physically interact with it. The first part focuses on sensing and estimation, covering proprioceptive methods such as odometry and inertial navigation, as well as exteroceptive vision-based techniques including camera…
This week explores how knowledge representation and reasoning (KRR) enable adaptive and goal-oriented robotic behavior. Learners examine how high-level knowledge is translated into executable actions, including planning as a search process, formal representation languages, and knowledge-based contr…
This week focuses on robotic manipulation, starting from the fundamental problem of grasping and its mathematical modeling. Learners explore grasp representations, friction constraints, and key tools such as the grasp matrix and hand Jacobian, extending to advanced concepts including compliance and…
Some points apply to every course of this kind; see how we rank.
Università di Napoli Federico II is in Tier 4: commercial training companies and platform-made courses of our institution ranking (66/100).
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