OVERVIEW

Different robotic agents can be employed for achieving a set of objectives via cooperative activities. From example, multiple sensoride vehicles can be employed for distributed area exploration, monitoring or surveying, while cooperating multi-mobile manipulators can be employed for manipulating, transporting and assembling objects. This course will present an efficient task-priority based control framework and its extension for the use in a cooperative context.

AIMS AND CONTENT

LEARNING OUTCOMES

The goal of the course is to first introduce a modern task-priority based control of robotic systems such as dual arm robots, mobile manipulators, floating underwater vehicle-manipulator systems, which are all characterized by a high number of degrees of freedom. The framework is extended to the case where multiple robots need to work together, for example to manipulate and transport objects cooperatively.

AIMS AND LEARNING OUTCOMES

At the end of the course the student will be able to design a modern task-priority kinematic controller. In particular, the student will be able to:

• Define control objectives for a robotic system
• Choose the appropriate priority levels for the control tasks
• Create different new control actions, as building blocks for the robotic system
• Know the extension to a cooperative manipulation case

The student will also have acquired:

• Advanced functional literacy competence
• Advanced personal competence
• Advanced social competence
• Proficiency in advanced project creation
• Competence in basic project management

PREREQUISITES

Students are required to know the fundamentals of kinematics.

TEACHING METHODS

The teaching modalities of this course are as follows.  
Approximately 20 hours are used to present the syllabus contents through regular lessons. The remaining hours are used for laboratory activities. In particular, a series of exercises of increasing difficulty are given and the class hours are exploited to solve them with the teacher's help. The exercises are carried out within a MATLAB simulation environment made available by the teacher. Two Franka Emika manipulators are made available in the laboratory for some of the assignments.

A continous assessment will be made on the exercises developed during the lessons.

Lessons attendance is mandatory.

The development of the final project (project-based learning), and related report, will enable the student to work on the skills

• advanced functional literacy competence
• advanced personal competence
• advanced social competence
• in advanced project creation
• in basic project management

Working students and students with certified DSA, disability or other special educational needs are advised to contact the lecturer at the beginning of the course to agree on teaching and examination arrangements that, while respecting the teaching objectives, take into account individual learning patterns.

SYLLABUS/CONTENT

The course will cover the following topics:

• Overview of the single agent control architecture
  • Basic definitions of relevant frames, actuation and sensory system
  • Hierarchical kinematic and dynamic control layers
• Task-priority control
  • Control objectives
  • Control tasks
  • Control Actions
  • Task-priority inverse kinematics
• Cooperative control
  • Extension of the task-priority for cooperative manipulation
  • Cooperative control for area coverage

RECOMMENDED READING/BIBLIOGRAPHY

The notes of the course will be available on Aulaweb and cover all the contents of the course.

For further readings, students can read the following books and papers:

• Siciliano, B., Sciavicco, L., Villani, L., Oriolo, G. (2009) Robotics: Modelling, Planning and Control. ISSN: 1439-2232
• Antonelli, G. (2018) Underwater robots. ISSN: 1610-7438
• Simetti, E., & Casalino, G. (2017). Manipulation and transportation with cooperative underwater vehicle manipulator systems. IEEE Journal of Oceanic Engineering, 42(4), 782-799.
• Simetti, E., & Casalino, G. (2016). A novel practical technique to integrate inequality control objectives and task transitions in priority based control. Journal of Intelligent & Robotic Systems, 84(1-4), 877-902.

TEACHERS AND EXAM BOARD

Exam Board

ENRICO SIMETTI (President)

FRANCESCO WANDERLINGH

GIOVANNI INDIVERI (President Substitute)

LESSONS

LESSONS START

https://courses.unige.it/11160/p/students-timetable

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Development of a project assigned during the course. The project is carried out in the MATLAB simulation environment used during the laboratory lessons.
The project requires the development of a task priority controller for a robotic system employed in a specific case study. The exam will be based on the discussion of the project and of the content covered during the lessons.

ASSESSMENT METHODS

At the end of the course, the student must be able to design a task priority controller for a given robotic system. This skill is evaluated through the discussion of the developed project (70%) and the continuous assessment during the lessons (30%).

The following items will be part of the evaluation:

• the correctness of the employed Jacobian relationships
• the student's ability in discussing the developed project
• which and how many tasks were successfully implemented by the robotic system