86477 - Industrial Robotics

Academic Year 2025/2026

  • Moduli: Alberto Martini (Modulo 1) Marco Troncossi (Modulo 2)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Advanced Automotive Engineering (cod. 9239)

Learning outcomes

Students learn the basic elements for modelling the kinematics, the statics and the dynamics of spatial articulated systems, which the current industrial robots are based on. In addition, the students learn basic knowledge of criteria of use, motion planning, as well as economic and organizational aspects that are needed to integrate robots into production systems.

Course contents

The course is organized in the following main sections:

  1. INTRODUCTION TO ROBOTICS. Introduction. Origins. State of the art of Robotics. Classification of robots. Aim of industrial Robotics. Main issues of industrial robotics. Precision and calibration.
  2. STRUCTURE AND GENERAL CHARACTERISTIC OF ROBOTS. Introduction. Structure of a robot. The manipulator. End effectors. Actuators. Sensors. Controller. Programming methods and languages. Main characteristics of an industrial robot.
  3. COORDINATE TRANSFORMATION MATRICES. Introduction. Position and orientation of a rigid body and reference systems. Matrices for the transformation of the coordinates. Rotations and translations. Homogeneous transformations.
  4. KINEMATICS OF MANIPULATORS. Introduction. Kinematic model of a manipulator. Matrices of Denavit-Hartenberg. Kinematic equations. Direct and inverse kinematic problem. Jacobian of a manipulator. Singularities.
  5. STATICS OF MANIPULATORS. Introduction. Analysis of forces and motion. Force and moments balancing.
  6. DYNAMICS OF MANIPULATORS. Introduction. Recall of rigid body dynamics. Equation of motion. Direct and inverse dynamic problem.
  7. TRAJECTORY PLANNING . Introduction. Generalities on the generation and description of the trajectory. Trajectory generation in Joint and Cartesian space. Trajectory planning based on the dynamic model.
  8. MANIPULATOR CONTROL. Introduction. Position control; Velocity control; Force control. Control systems of existing industrial robots.
  9. MANAGEMENT AND ECONOMIC ASPECTS (hints). Industrial robotics standards. Organization and automation impacts on production.
  10. PROBLEMS AND APPLICATIONS.

Readings/Bibliography

Reference book

  • Siciliano B., Sciavicco L., Villani L., Oriolo G., Robotics: Modelling, Planning and Control, Springer, 2009.

Suggested book

  • Siciliano & Khatib eds., Handbook of Robotics, Springer, New York, 2008

In-depth readings

  • Tsai L.W., Robot Analysis, The Mechanics of Serial and Parallel Manipulators, John Wiley & Sons, 1999.
  • Merlet J.P., Parallel robots. Kluwer, Dordrecht, 2000.
  • Nof S.Y., Handbook of Industrial Robotics, 2nd ed., John Wiley & Sons, 1999.
  • Engelberger J.F., Robotics in Practice: Management and applications of industrial robots, Avebury Publishing Company, 1980.
  • Craig J., Introduction to Robotics, Mechanics and Control, 1989, Addison-Wesley Publishing Company.
  • Erdman and Sandor, Analysis and Synthesis of Mechanisms, voll. 1 and 2, 1990, Prentice-Hall.
  • Suh C.H. and Radcliffe C. W., Kinematics and Mechanisms Design, John Wiley & Sons, 1978.
  • Sandler Ben-Zion, Robotics: Designing the Mechanisms for Automated Machinery, Academic Press, 1999.
  • Rivin, E. I. Mechanical design of Robots, McGraw-Hill, 1988.

Teaching methods

The course includes:

  1. Theoretical lectures conducted on the blackboard and with the aid of multimedia systems.
  2. A complete cycle of exercises and illustration of industrial applications that combines and integrates theoretical lessons.
  3. Introduction to the use of simulation software.

Lessons taught in lecture room and in computer lab.

In consideration of the type of activity and the teaching methods adopted, the attendance of this training activity requires the prior participation of all students in the training modules 1 and 2 on safety [https://elearning-sicurezza.unibo.it/], in e-learning mode.

Assessment methods

To be admitted to the exam, students must work on a group project (2 or 3 people) concerning the optimization of the tasks of an industrial robot, by using the tools illustrated during the course (including software for numerical simulation).
The final examination consists of the discussion of the project and two oral questions on the program of the entire course (about 10-15 minutes for each question). The candidate may be required to draw schematics and/or to write expressions/equations with pen and paper. The candidate must achieve a sufficient score (18 out of 30) for the project and for each question in order to pass the exam. The score is assigned on the basis of:
[project]
• Correctness and effectiveness of the adopted approach (50 %)
• Accuracy of the final results (30 %)
• Clarity in exposition and proper use of technical terminology (20 %)
[oral questions]
• Knowledge of the specific topic (40 %)
• Ability to analyze and discuss different scenarios and possible interactions with other topics (30 %)
• Clarity in exposition and proper use of technical terminology (30 %)
The final grade is computed as the weighted average of the three scores (project 50%, questions 25% each).

For each exam session, students that were granted the status of "working student" may ask to replace one of the dates of the session with another date. Students must contact the teacher at least 14 days before the first exam date of the session, in order to define a feasible date considering all the collected requests.

In compliance with the Art. 16 of the University Didactic Regulations, after a positive final grade has been assigned, the student can decide to retake the exam only once.

Teaching tools

Slides are used as a support for the lesson presentations. Pdf files of the presentations (along with suggested readings, lesson notes and additional supplementary material) are available at https://virtuale.unibo.it [https://virtuale.unibo.it/]

Office hours

See the website of Alberto Martini

See the website of Marco Troncossi

SDGs

Quality education Industry, innovation and infrastructure

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.