A fuzzy speed controller for a guide robot using an HRI approach Article uri icon

abstract

  • Assistant mobile robots are designed to help people in diverse situations. To improve services provided, robots should keep close to the user. In this work, it is implemented a Human-Robot Interaction (HRI) approach for a guide robot application, where a fuzzy controller is proposed for adjusting the robots speed based on the estimated users speed. User velocity is computed with a vision algorithm which estimates users position along a path. The guide process begins when the robot recognizes the user and then it proposes to guide him from an initial point to a given goal. To stay close to the user, the robot adjusts its linear velocity with a fuzzy PI D controller. The reference signal of this controller is the users velocity and the output is the linear velocity of the robot. To follow the correct path simultaneously, it has been implemented a second control based on fuzzy logic to manipulate the angular velocity of the robot over the given path. The results obtained for both controllers show that the robot is able to track a velocity reference along a path and follow a desired goal trajectory. To guarantee safe and efficient interaction between people and robot, social rules were established. © 2003-2012 IEEE.
  • Assistant mobile robots are designed to help people in diverse situations. To improve services provided, robots should keep close to the user. In this work, it is implemented a Human-Robot Interaction (HRI) approach for a guide robot application, where a fuzzy controller is proposed for adjusting the robots speed based on the estimated users speed. User velocity is computed with a vision algorithm which estimates users position along a path. The guide process begins when the robot recognizes the user and then it proposes to guide him from an initial point to a given goal. To stay close to the user, the robot adjusts its linear velocity with a fuzzy PI%2bD controller. The reference signal of this controller is the users velocity and the output is the linear velocity of the robot. To follow the correct path simultaneously, it has been implemented a second control based on fuzzy logic to manipulate the angular velocity of the robot over the given path. The results obtained for both controllers show that the robot is able to track a velocity reference along a path and follow a desired goal trajectory. To guarantee safe and efficient interaction between people and robot, social rules were established. © 2003-2012 IEEE.

publication date

  • 2018-01-01