Fundamentals of Robotics
Knowledge about industrial robots and modelling of robot kinematics and dynamics. Ability to plan robot motion and execute planned trajectories. Knowledge of basic robot control principles and design methods. Understanding of robotized manufacturing systems.
- create a kinematic model of a robot (direct and inverse kinematics)
- create a dynamic model of a robot (Lagrange-Euler, Newton-Euler)
- generate trajectories for Point-to-point and Continuous-path robot motion
- design robot joint position control systems
- design of robot force control
- synthesize robot control in the manufacturing system
Forms of Teaching
Lectures are organized in thematic cycles and comply with the exercises in the course Control Laboratory 1. Direct communication with students during lectures.Exams
At least three home works must be presented (defended) in the class by randomly selected students.Exercises
Can be organized if students ask for it.Laboratory Work
Laboratory exercises are carried out in the course Control Laboratory 1.Consultations
One hour weekly.
|Type||Threshold||Percent of Grade||Threshold||Percent of Grade|
|Homeworks||50 %||20 %||50 %||20 %|
|Mid Term Exam: Written||50 %||25 %||0 %|
|Final Exam: Written||50 %||25 %|
|Final Exam: Oral||30 %|
|Exam: Written||50 %||50 %|
|Exam: Oral||30 %|
The oral exam share is ±30%. Homeworks are obligatory.
Week by Week Schedule
- Video presentation: ABB Robot Systems, Application of robots in manufacturing of Mercedes and BMW. Robot types and characteristics.
- Types and characteristics of robot elements. Position and orientation of a rigid body. Quaternions. Denavit-Hartenberg convention.
- Direct kinematics. Examples of solving a forward kinematics problem.
- Inverse kinematics. Solving methods. Examples of solving an inverse kinematics problem.
- Dynamic robot modeling. Lagrange-Euler method of dynamic modeling.
- Newton-Euler method of dynamic modeling. Examples of N-E dynamic robot modeling.
- Trajectory planning. Point-to-point (PTP) robot motion planning. Interpolation methods. Taylor bounded deviation method.
- Midterm exam
- Continuous path (CP) robot motion planning. Ho-Cook trajectory planning method. Examples of trajectory planning with Ho-Cook method.
- Robotic drives and drive control systems. Synthesis of nominal robot control. Servo systems synthesis methods (PI and PDFF controller).
- Robot joint position control with joint torque control. PD position control with added compensations. Hsia method of robust position control.
- Robot joint position control with joint velocity control. PD position control with PI speed control. CNC-based robot joint position control.
- Robot force control. Hybrid robot force control.
- Robot impedance control.
- Final exam