- 25.12.2018 Final Exam is today in CMPE033 (15.01.2019 Tuesday at 12.30). All material included.
- 25.12.2018 Midterm/Final Questions (PDF)
- 15.12.2018 Fuzzy sets and Systems (PDF)
- 15.12.2018 Image and Vision (PDF)
- 14.12.2018 Actuators and Sensors (PDF)
- 4.12.2018 Project (PDF)
- 4.12.2018 Trajectory planning (PDF)
- 12.11.2018 Dynamics (PDF)
- 22.10.2018 Jacobian (Velocities) (PDF)
- 10.10.2018 CourseBook (PDF)
- 9.10.2018 Homework1&2 (PDF). Due to 16.10.2018.
- 2.10.2018 Kinematics (PDF) ,
- 27.09.2018 Introduction (PDF).
Course Contents (in weeks):
1. Introduction to robotics, definition, history, classification, applications, and social issues.
2. Robot kinematics: Position Analysis: Manipulator mechanisms,
3. Matrix representation and homogeneous transformation matrices Representation of Transformation and Inverse Transformation Matrices,
4. Denavit-Hartenberg representation of forward and Inverse Kinematics (16.10.2018)
5. Differential Motions and Velocities: Jacobian, differential motion of a frame
6. Interpretation of the Differential Change, calculation of Jacobian. Inverse Jacobian.
7. Dynamic Analysis and Forces: Lagrangian Mechanics
8. Effective Moments of Inertia, Dynamic Equations for Multiple Degree of Freedom Manipulators. Transformation of forces and Moments between Coordinate Frames
9. Trajectory Planning: Path vs. trajectory. Joint and Cartesian Space. Trajectory recording.
10. Actuators: Characteristics of electrical, hydraulic and pneumatic devices. Microprocessor control.
11. Sensors: Characteristics for position, velocity, acceleration, force and torque sensors. Proximity, range-finder, sniff sensors.
12. Vision and Voice recognition/synthesis systems. Image Processing vs. Image Analysis, Image Types, Digital images, Frequency and Spatial Domains, Noise, Edge, Convolution Mask, Sampling Theorem, Histogram of images, Edge Detection, Segmentation, Binary and Gray Morphology Operations,
13. Image Analysis: Object recognition by features, Image Data Compression, Real Time Image Processing
14. Fuzzy Logic Control: Crisp and Fuzzy values, Fuzzy Sets, Fuzzification, Fuzzy Rule Base and Fuzzy inference, Defuzzification, Simulation of Fuzzy Logic Controller. Applications of Fuzzy Logic in Robotics.
Saeed B. Niku, Introduction to Robotics, Analysis, Systems, Applications (irsn), Prentice Hall, 2001, ISBN 0-13-061309-6
M.Bodur, Robotics Course Notes, 2006.
Course Description and Objective:
Robotics is a major application field of Computational Intelligence and Mechatronics. A robotics course is specified as an essential technical elective course both by IEEE and ACM, the two international occupational institution of computer engineering. A robotics course is essential in all three legs of Mechatronics: Mechanical, Electronics, and Computer Engineering. This course is especially tailored for Computer Engineers in a design-oriented format.
This robotics course consists of an introduction to robotics, the kinematics of manipulators, differential motion relations, robot dynamics, path and trajectory planning, actuators, sensors, vision systems, and computational intelligence through fuzzy logic. The course include project to develop a software for each section of the course material, yielding to a intelligent robotic simulation tool.
The objective of the course is to cover the kinematics, dynamics and path planning together with the important subsystems such as image processing and vision, sensory, programming, decision, and fuzzy rule based intelligence systems in an introductory level. The course may be equivalently useful both for the advanced studies in Computer Engineering and for a senior level technical elective purpose.
HW and Projects: