• 052367 - CONTROL OF INDUSTRIAL ROBOTS

The goal of this course is to present current and advanced methodologies for the control of robotic manipulators. The course covers selected topics ranging from kinematic and dynamic modelling of an industrial robot, to motion planning and control, to control of the interaction of the robot with the environment. The goal of the course is fully aligned with the overall goals of the Automation and Control Engineering Program, while being an excellent complement for students enrolled in other Programs (Computer Science and Engineering, Electronics Engineering, Engineering Physics, and others).

A mix of theoretical and industrially relevant topics characterizes the course, where extensive use of software for simulation and offline programming of robots will be made.

The expected learning outcomes of the course belong to the technological and design area of the expected learning outcomes of the Program.

Specifically, at the end of the course, the student is expected to be able to:

-understand the role of industrial robots in the factory, why and where they should be used in the production systems;

-use mathematics to describe the motion of a robot;

-plan a suitable motion for the robot both in free environment and in presence of obstacles;

-tune an industrial motion control system and understand the rationale and potentialities of advanced nonlinear model based control strategies;

-manage the control of the interaction of the robot with the environment, either with force or with vision sensors;

-understand and master the new trends in industrial robotics, like collaborative robotics;

-use software programs to simulate and to offline program the robots.

1. Introduction: Industrial robots: basic concepts and examples. Market of industrial robotics. Trends in industrial robotics.

2. Robot kinematics: Review of direct, inverse and differential kinematics. Kinematics of redundant manipulators. Inverse differential kinematics.

3. Robot dynamics: Dynamic models of robot manipulators. Euler-Lagrange and Newton-Euler formulations. Main properties. Identification of dynamic parameters. Direct and inverse dynamics.

4. Motion planning: Path planning and trajectory planning. Trajectories in the joint space: point to point motion and interpolation of points (splines). Kinematic and dynamic scaling of trajectories. Trajectories in the operational space : position and orientation trajectories. Robot programming languages: examples. Path planning with obstacle avoidance.

5. Control of robot manipulators: Approximate decentralized model of the robot. Review of independent joint control methods. Centralized model-based controllers. Computed torque feedforward control. PD control with gravity compensation. Inverse dynamics control. Robust and adaptive control. Operational space control.

6. Interaction with the environment: Force sensors. Impedance and admittance control. Hybrid position/force control.

7. Control with vision sensors: Components of a visual system. Image processing. Image-based and position-based visual servoing.

Some of the practice sessions will make use of computer simulation tools and of commercial tools for robot offline programming.

Students attending this course are expected to know basics of mechanics and of automatic control.

The final assessment will be a written exam, consisting of both numerical exercises and theoretical questions.

In the written exam the student should be able to:

-compute the dynamic model of simple two degrees of freedom robots;

-compute or rescale a trajectory in joint space or in the operational space;

-tune the joint controller for an independent joint control industrial system;

-discuss the main properties of centralized model-based controllers;

-discuss the main properties of the control with force and vision sensors and solve simple numerical related design problems.