scholarly journals Vision-based vanishing point detection of autonomous navigation of mobile robot for outdoor applications

2021 ◽  
Vol 12 (2) ◽  
pp. 117-125
Author(s):  
Leonard Rusli ◽  
Brilly Nurhalim ◽  
Rusman Rusyadi

The vision-based approach to mobile robot navigation is considered superior due to its affordability. This paper aims to design and construct an autonomous mobile robot with a vision-based system for outdoor navigation. This robot receives inputs from camera and ultrasonic sensor. The camera is used to detect vanishing points and obstacles from the road. The vanishing point is used to detect the heading of the road. Lines are extracted from the environment using a canny edge detector and Houghline Transforms from OpenCV to navigate the system. Then, removed lines are processed to locate the vanishing point and the road angle. A low pass filter is then applied to detect a vanishing point better. The robot is tested to run in several outdoor conditions such as asphalt roads and pedestrian roads to follow the detected vanishing point. By implementing a Simple Blob Detector from OpenCV and ultrasonic sensor module, the obstacle's position in front of the robot is detected. The test results show that the robot can avoid obstacles while following the heading of the road in outdoor environments. Vision-based vanishing point detection is successfully applied for outdoor applications of autonomous mobile robot navigation.

Robotics ◽  
2010 ◽  
Author(s):  
H. Wicaksono ◽  
K. Anam ◽  
P. Hastono ◽  
I.A. Sulistijono ◽  
S. Kuswadi

2012 ◽  
Vol 2 (2) ◽  
Author(s):  
B. Deepak ◽  
Dayal Parhi

AbstractA novel approach based on particle swarm optimization has been presented in this paper for solving mobile robot navigation task. The proposed technique tries to optimize the path generated by an intelligent mobile robot from its source position to destination position in its work space. For solving this problem, a new fitness function has been modelled, which satisfies the obstacle avoidance and optimal path traversal conditions. From the obtained fitness values of each particle in the swarm, the robot moves towards the particle which is having optimal fitness value. Simulation results are provided to validate the feasibility of the developed methodology in various unknown environments.


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