Abstract
This paper addresses the problem of making a non-holonomic wheeled mobile robot (WMR) move to a target object using computer vision and obstacle-avoidance techniques. If a priori information about the obstacles is available, pre-planning the desired path can be a good candidate method. However, in so many cases, obstacles are dynamic. Therefore, our first challenge is to make the WMR move to a desired target while autonomously avoiding any obstacle along its path. The second challenge deals with visual-tracking loss; that is, when the target is lost from the camera scope, the robot should use Dead Reckoning (DR) to get back on its path towards the target. The Visual Tracking (VT) algorithm then takes the relay to reach the final destination, compensating for any errors due to DR by calculating the distance to the target when it is within the scope of the camera. The proposed system also uses two fuzzy-logic controllers; the first controller avoids objects while the second manages the path to the target. Different complex scenarios have been implemented, showing the validity of our multi-controller model.
Highlights
Visual Tracking (VT) is considered to be a very important tool in robotic applications, especially for navigation within unknown and dangerous environments
A hybrid visual-servoing controller was pro‐ posed in [3]to drive a mobile robot equipped with a fivedegrees-of-freedom (5-DOF) arm towards a target and to autonomously grasp and manipulate the target
Once the target is found, the system enters a loop that begins by reading the values of the sonar sensors, after which the robot starts to move towards the target using the Go-to-target Fuzzy Logic Controller (GTFLC) controller
Summary
VT is considered to be a very important tool in robotic applications, especially for navigation within unknown and dangerous environments. A hybrid visual-servoing controller was pro‐ posed in [3]to drive a mobile robot equipped with a fivedegrees-of-freedom (5-DOF) arm towards a target and to autonomously grasp and manipulate the target. The authors in [4]developed a method for controlling a twowheeled robotic manipulator with visual servoing by using a stereo vision system to detect the size, distance and relative position of the desired target. All of these investi‐ gations used only visual servoing, which requires the presence of the object within the tracked scene during servoing. In [10], the authors proposed a method to make a robot move and avoid obstacles in dynamic environmentsusinga combination of fuzzy logic (FL) and DR, but their method required preloaded target information
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