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Robotics and autonomous robotics modeling (09_O-MRA) ​

  • Coefficient : 6
  • Hourly Volume: 150h (including 72h supervised)
    CM : 36h supervised
    TD : 18h supervised (and 6h unsupervised)
    Labo : 18h supervised (and 6h unsupervised)
    Out-of-schedule personal work : 66h

AATs Lists

Description ​

  • Skills: The first skill is knowing how to develop, using methods shared by all roboticists, geometric, kinematic and dynamic models, allowing the engineering and control of industrial robots. The second is the engineering of autonomous mobile robots through modeling, perception and control. Control is addressed in the context of in-plane wheeled mobile robots.
  • Program :
    • Modeling in Industrial Robotics - P1
    • general principles, 3D rotations, base changes, homogeneous matrices
    • geometric modeling (positions, orientations, inversion, degrees of freedom)
    • kinematic modeling (Jacobian matrix, inversion, kinematic singularities)
    • dynamic modeling (Newton-Euler method and double-recursive formalism)
    • Application: Modeling of the IRB140 carrier, numerical simulations (Scilab)
    • Mobile and Autonomous Robotics - P2
    • introduction, areas and applications of mobile robotics
    • techniques for modeling and perception of wheeled locomotion
    • in-plane, model-based control-command of wheeled mobile robots
    • Application: Labs or Mini Projects with LEGO Mindstorms robots (EV3)

Learning Outcomes AAv (AAv) ​

1. Modeling in Industrial Robotics - P1

  • AAv1 [heures: 12.5, A3, B2, B3] : At the end of the semester, MRA students will be able to understand and characterize the different spaces in which the robot evolves and describe the models and their associated characteristics, making the connections between them.

  • AAv2 [heures: 12.5, A3, B1, B2, B3, D2] : At the end of the semester, MRA students will be able to obtain the direct geometric model of a serial robot, with rotoid and prismatic connections, using either a kinematic diagram, or from the analysis of the axes of a real robot.

  • AAv3 [heures: 12.5, A3, B1, B2, B3, D2] : At the end of the semester, MRA students will be able to obtain the direct and inverse kinematic model of a serial robot, with rotoid and prismatic connections, using either a kinematic diagram or by analyzing a real robot.

  • AAv4 [heures: 12.5, A3, B1, B2, B3, D2] : At the end of the semester, MRA students will be able to obtain the direct and inverse static model of a serial robot, with rotoid and prismatic connections, using either the geometric model and/or the kinematic diagram of the robot.

  • AAv5 [heures: 12.5, A3, B1, B2, B3, D2] : At the end of the semester, MRA students will be able to obtain the dynamic model of a serial robot, with rotoid and prismatic connections, in the form of a system of nonlinear differential equations, using the kinetostatic model and the double recursive Newton-Euler method.

  • AAv6 [heures: 12.5, C1, C2, D3] : At the end of the semester, MRA students will be able to interact the different models of a robot (geometric, kinematic and dynamic) within a simulation program /command in high-level programming (Scilab).

2. Mobile and Autonomous Robotics - P2

  • AAv7 [heures: 18.75, B3, B4] : At the end of the semester, MRA students will be able to calculate the planar kinematic model of wheeled robots

  • AAv8 [heures: 18.75, B3, C1] : At the end of the semester, MRA students will be able to design the in-plane perception/localization system of a wheeled robot.

  • AAv9 [heures: 18.75, B2, C1, C2, D3] : At the end of the semester, MRA students will be able to synthesize the system and control laws of wheeled mobile robots, based on the model

  • AAv10 [heures: 18.75, C3, D1, D3] : At the end of the semester, MRA students will be able to implement a theoretical solution in mobile robotics (structure, mechatronic assembly and programming) on ​​an existing physical support (platform type LEGO robots).

Assessment methods ​

Average of several assesments

Key Words ​

Denavit & Hartenberg, Euler parameters, geometric model, inversion, decoupling, singularities, redundancy, Euler-Newton, autonomy, perception, localization, navigation, control.## Prerequisites

Prerequisites ​

Vector analysis, trigonometry, kinematics and solid dynamics, linear algebra, Scilab programming, linear automation, digital integration and derivation.

Resources ​

  1. Handbook of Robotics – Siciliano-Khatib Eds
  2. Introduction to Autonomous Mobile Robots - R. Siegwart, I.R. Nourbakhsh
  3. Mathematical Control Theory: Deterministic Finite Dimensional Systems. Eduardo D. Sontag. Springer; 2nd ed. 1998.
  4. Analysis and Control of Nonlineac Systems - Jean Lévine, Springer, 2009