Aims and learning outcomes

This course will present current and advanced methodologies for the control of robotic manipulators. After the review of some basic elements in robot kinematics, and the presentation of a few advanced topics, the dynamic model of the manipulator will be discussed, along with its main properties. The control of the manipulator will be addressed both in terms of motion planning and in terms of feedback control. Path and trajectory planning in joint space and in Cartesian space will be presented, together with advanced topics such as kinematic and dynamic scaling of trajectories and obstacle avoidance. Concerning the feedback control, independent joint control techniques will be first discussed, with emphasis on the role of the flexibility in the joints, then advanced model-based centralized controllers will be studied. The final part of the course will be devoted to the control of robots with external sensors, including both force sensors to control the physical interaction with the environment and vision sensors to model the environment and achieve visual servoing of the manipulator.

Syllabus

1. Introduction: Industrial robotics. Robots, applications, trends.

2. Robot kinematics: Quick 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. Joint space trajectories: point to point motion and interpolation of points (splines). Kinematic and dynamic scaling of trajectories. Cartesian space trajectories: position and orientation trajectories. Path planning with obstacle avoidance. Robot programming: examples.

5. Control of robot manipulators: Review of independent joint control methods. Advanced schemes for joint control. Computed torque feedforward control. PD control with gravity compensation. Inverse dynamics control. Robust and adaptive control. Operational space control.

6. Interaction with the environment: Compliance control, impedance control, hybrid position/force control.

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

Laboratory activities

Some of the training sessions will make use of computer simulation tools.

Prerequisites

Basics of Automatic Control and Mechanics.

Students will take a written examination, integrated by an oral one at the instructor’s discretion