Collision avoidance and trajectory tracking control based on approximations of the maximum function

2010 ◽  
Author(s):  
J S Mejia ◽  
K Srivastava ◽  
D M Stipanovic
Keyword(s):  
Collision Avoidance ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Maximum Function ◽  
Trajectory Tracking Control

Trajectory Tracking Control of Unicycle Robots with Collision Avoidance and Connectivity Maintenance

2019 ◽  
Vol 96 (3-4) ◽  
pp. 331-343 ◽  
Author(s):  
Mansour Karkoub ◽  
Gokhan Atınç ◽  
Dusan Stipanovic ◽  
Petros Voulgaris ◽  
Andy Hwang
Keyword(s):  
Collision Avoidance ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Trajectory Tracking Control ◽  
Connectivity Maintenance ◽  
Unicycle Robots

Trajectory tracking control with obstacle avoidance capability for unicycle-like mobile robot

2012 ◽  
Vol 60 (3) ◽  
pp. 537-546 ◽  
Author(s):  
W. Kowalczyk ◽  
M. Michałek ◽  
K. Kozłowski
Keyword(s):  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Trajectory Tracking ◽  
Avoidance Behavior ◽  
Tracking Control ◽  
Local Characteristic ◽  
Trajectory Tracking Control ◽  
Real Robot ◽  
Artificial Potential Function ◽  
The Stability

Abstract In this paper the trajectory tracking control algorithm with obstacle avoidance capability is presented. As a robot gets into a neighborhood of the obstacle, the collision avoidance behavior is turned on. It is implemented using the artificial potential function (APF) that increases to infinity as the robot approaches a boundary of the obstacle. This feature guarantees collision avoidance. As avoidance behavior is active only in the neighborhood of the obstacle it does not affect the motion when there is no risk of the collision. Authors show that trajectory of the robot converges to desired one when a robot is out of the APF area. Due to a local characteristic of the APF, the implementation of the algorithm of the robot that uses only on-board sensors is possible. The stability proof is presented for both a near obstacle and obstacle-free areas. Effectiveness of the algorithm is illustrated with experiments on a real robot in an environment with static circle-shaped obstacles.

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