Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Robotic Methodologies

University of Naples Federico II via Coursera

Go to class Write review

Details

Go to class

Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

4 weeks, 3 hours a week
Sessions

Self-Paced
Level

Intermediate
Subtitles

English

Found in

Part of

Robotics & Robots

Overview

Google, IBM & Meta Certificates – 40% Off

One plan covers every Professional Certificate on Coursera.

Unlock All Certificates

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

Syllabus

Foundations and Ethics of Robotics

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 part of the week focuses on roboethics, addressing key ethical frameworks and real-world dilemmas related to autonomous systems, including applications in healthcare, autonomous driving, and human labor. Through case studies and conceptual analysis, learners examine responsibility, decision-making, and the concept of meaningful human control in modern robotics.

Perception and Physical Interaction

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 modeling, calibration, triangulation, and 3D perception through point cloud registration. The second part addresses force control and compliant interaction, introducing impedance and admittance control, multi-degree-of-freedom systems, and hybrid force/motion control strategies for constrained tasks such as peg-in-hole operations. Through these topics, learners gain a unified view of perception and interaction as tightly coupled processes in robotic systems.

Reasoning and Mobile Systems

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 control architectures. The role of digital twins is introduced as a powerful framework for integrating knowledge, simulation, and real-world interaction. The week concludes with wheeled robots, analyzing mobility principles, design choices, and their use in real-world applications. Learners explore how decision-making and motion are integrated in autonomous systems.

Manipulation and Cooperation

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 postural synergies in robotic hands. The second part introduces cooperative manipulators, highlighting the motivations, modeling approaches, and control strategies for multi- robot manipulation. The week provides both theoretical foundations and insights into recent developments in coordinated manipulation.