1 / 20

Autonomous vehicle navigation An Obstacle Avoidance Exercise Luca Baglivo, Mariolino De Cecco

Autonomous vehicle navigation An Obstacle Avoidance Exercise Luca Baglivo, Mariolino De Cecco. We ’ re using two-dimensional grids: maps represented as images !. Example from CAD to Image. Let’s consider the following simplified scenario:. Goal. Start. +. ATTRACTIVE POTENTIAL.

ocrum
Télécharger la présentation

Autonomous vehicle navigation An Obstacle Avoidance Exercise Luca Baglivo, Mariolino De Cecco

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Autonomous vehicle navigation An Obstacle Avoidance Exercise Luca Baglivo, Mariolino De Cecco

  2. We’re using two-dimensional grids: maps represented as images!

  3. Example from CAD to Image

  4. Let’s consider the following simplified scenario: Goal Start

  5. + ATTRACTIVE POTENTIAL REPULSIVE POTENTIAL … AND IMAGINE ROBOT AS A BALL ROLLING DOWN HILLS

  6. TOTAL POTENTIAL

  7. POTENTIAL FIELDS METHOD FEATURES: • AUTOMATIC PATH PLANNING FOR OBSTACLE AVOIDANCE • IS BOTH A PLANNING & CONTROL STRATEGY ALL-IN-ONE • BEST FOR LOCAL PATH PLANNING->UNEXPECTED OBSTACLES • BE AWARE FROM LOCAL MINIMA! HARMONIC POTENTIAL FUNCTIONS HAS PROVEN ONLY GLOBAL MINIMA • NOT SUITABLE FOR HIGH PRECISION POSITIONING ON TARGET

  8. A FORMULATION

  9. A FORMULATION

  10. A FORMULATION

  11. A FORMULATION

  12. A FORMULATION

  13. THE RESULTING FORCE IS THE GRADIENT AND GIVES DIRECTION TO THE ROBOT This example is in the Matlab script “OstacoliQuadrati.m”

  14. ANOTHER, NAIVE FORMULATION A VIRTUAL CORIDOR ALIGNMENT FOR LINE FOLLOWING • The attractive potential can be defined punctually as desired. • Build a vector field that point towards desired path.

  15. ANOTHER, NAIVE FORMULATION A VIRTUAL CORRIDOR ALIGNMENT FOR LINE FOLLOWING • How to define it yF alphaK angles (+) y K xF Lc

  16. ANOTHER, NAIVE FORMULATION A VIRTUAL CORIDOR ALIGNMENT FOR LINE FOLLOWING • How to compute steering angle input aK d y K steering axis

  17. ANOTHER, NAIVE FORMULATION A VIRTUAL CORIDOR ALIGNMENT FOR LINE FOLLOWING • Now add the repulsive force vector Frep, and play … Frep Ftot delta’ y K

  18. ANOTHER, NAIVE FORMULATION A VIRTUAL CORIDOR ALIGNMENT FOR LINE FOLLOWING • A control sketch y Potential field gradient vector velocity Robot kinematic model alphaK steer angle - delta + Steer control kcontrol

  19. ANOTHER, NAIVE FORMULATION A VIRTUAL CORIDOR ALIGNMENT FOR LINE FOLLOWING • Try with: • Tricycle robot forward velocity, point obstacle at (xF,yF) = (4,1.5) D1 yR b

  20. Bibliography Siegwart R., Nourbakhsh I, Scaramuzza D., Introduction to Autonomous Mobile Robots

More Related