Introduction to Robotics (ME 403)

2019 Spring
Faculty of Engineering and Natural Sciences
Mechatronics(ME)
3
6.00 / 6.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Volkan Pato─člu vpatoglu@sabanciuniv.edu,
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English
Undergraduate
ENS206
Formal lecture,Recitation,Laboratory
Interactive,Discussion based learning,Project based learning,Simulation,Case Study
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CONTENT

This course is intended to present fundamentals of robotic systems. Specific subjects include: position and orientation in 3-D space; manipulator forward and inverse kinematics; velocities and forces - Jacobian's relations; manipulator dynamics; stiffness and compliance control; trajectory control; mobile robots - selected topics. A team project will emphasize the variety of robotics system

OBJECTIVE

This course is designed to equip students with fundamental theories and computational methodologies that are used in design and analysis of robotic systems. Students will learn how to analytically formulate kinematic and dynamic equations for robot manipulators, how to synthesize trajectory and force tracking controllers, as well as how to utilize numerical algorithms to simulate and real-time hardware-in-the-loop controllers to implement such closed-loop control systems.

During the fi rst part of the course, students will be introduced to rigid motions in space and homogeneous transformations, forward and inverse kinematics at confi guration and velocity levels, and Lagrange's equations. Computer-aided dynamic simulations with numerical time integration methods will be exercised.

During the second part of the course, students will be introduced to path and trajectory planning methods, as well as fundamental techniques for robot control. In particular, independent joint control, multi-variable control, force and impedance control approaches will be introduced and implemented on hardware.

The emphasis in this course is an integrated understanding of the kinematic/dynamic modeling and control concepts for robotic manipulators. Real-time hardware-in-the-loop implementation of the controllers is also emphasized such that students can experience the control challenges of the real world, such as sensor noise and unmodeled system dynamics.

This course involves a hands-on laboratory component (ME 403L) and a team project where the students are expected to implement their algorithms on sample robotic platforms.

LEARNING OUTCOME

On successful completion of the course;
students will learn how to analytically formulate kinematic and dynamic equations for robot manipulators,
how to synthesize trajectory and force tracking controllers, and
how to utilize numerical algorithms to simulate and real-time hardware-in-the-loop controllers to implement such closed-loop control systems.

PROGRAMME OUTCOMES


1. Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 2

2. Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 4

3. Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects. 4

4. Communicate effectively in Turkish and English by oral, written, graphical and technological means. 3

5. Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 5


1. Possess sufficient knowledge of mathematics, science and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 5

2. Identify, define, formulate and solve complex engineering problems; choose and apply suitable analysis and modeling methods for this purpose. 5

3. Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; possess knowledge of standards used in engineering applications; use information technologies effectively. 5

4. Ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose. 5

5. Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas. 5

6. Knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development. 4

7. Knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; understanding of professional and ethical responsibility. 3


1. Familiarity with concepts in statistics and optimization, knowledge in basic differential and integral calculus, linear algebra, differential equations, complex variables, multi-variable calculus, as well as physics and computer science, and ability to use this knowledge in modeling, design and analysis of complex dynamical systems containing hardware and software components. 5

2. Ability to work in design, implementation and integration of engineering applications, such as electronic, mechanical, electromechanical, control and computer systems that contain software and hardware components, including sensors, actuators and controllers. 5


1. Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem. 3

2. Demonstrate knowledge of discrete mathematics and data structures. 1

3. Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering. 1


1. Formulate and analyze problems in complex manufacturing and service systems by comprehending and applying the basic tools of industrial engineering such as modeling and optimization, stochastics, statistics. 1

2. Design and develop appropriate analytical solution strategies for problems in integrated production and service systems involving human capital, materials, information, equipment, and energy. 1

3. Implement solution strategies on a computer platform for decision-support purposes by employing effective computational and experimental tools. 1


1. Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 1

2. Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems. 1

3. Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa. 1


1. Comprehend key concepts in biology and physiology, with emphasis on molecular genetics, biochemistry and molecular and cell biology as well as advanced mathematics and statistics. 1

2. Develop conceptual background for interfacing of biology with engineering for a professional awareness of contemporary biological research questions and the experimental and theoretical methods used to address them. 1

ASSESSMENT METHODS and CRITERIA

  Percentage (%)
Final 20
Midterm 20
Assignment 18
Participation 2
Group Project 20
Homework 20

RECOMENDED or REQUIRED READINGS

Textbook

Mark W. Spong, Seth Hutchinson, M. Vidyasagar, Robot Modeling and Control, John
Wiley & Sons, Inc., 2006.

Readings

John J. Craig, Introduction to Robotics: Mechanics and Control, Prentice Hall, 2004.

Course Web https://sucourse.sabanciuniv.edu/portal/site/ME403-201502