scholarly journals SWITCHER: A Stereo Algorithm for Ground Plane Obstacle Detection

1989 ◽  
Author(s):  
Y. Zheng ◽  
D. G. Jones ◽  
S. A. Billings ◽  
J. E. W. Mayhew ◽  
J. P. Frisby
Keyword(s):  
Ground Plane ◽  
Obstacle Detection ◽  
Plane Obstacle ◽  
Stereo Algorithm

scholarly journals SWITCHER: a stereo algorithm for ground plane obstacle detection

1990 ◽  
Vol 8 (1) ◽  
pp. 57-62 ◽  
Author(s):  
Y Zheng ◽  
DG Jones ◽  
SA Billings ◽  
JEW Mayhew ◽  
JP Frisby
Keyword(s):  
Ground Plane ◽  
Obstacle Detection ◽  
Plane Obstacle ◽  
Stereo Algorithm

scholarly journals Ground Plane Obstacle Detection under variable Camera Geometry Using a Predictive Stereo Matcher

BMVC92 ◽  
1992 ◽  
pp. 548-559
Author(s):  
Stuart Cornell ◽  
John Porrill ◽  
John E. W. Mayhew
Keyword(s):  
Ground Plane ◽  
Obstacle Detection ◽  
Plane Obstacle

Real-time ground plane segmentation and obstacle detection for mobile robot navigation

INTERACT-2010 ◽  
2010 ◽  
Author(s):  
Arshad Jamal ◽  
Praveen Mishra ◽  
Subrata Rakshit ◽  
Abhishekk Kumar Singh ◽  
Manish Kumar
Keyword(s):  
Mobile Robot ◽  
Real Time ◽  
Robot Navigation ◽  
Ground Plane ◽  
Obstacle Detection ◽  
Mobile Robot Navigation

Obstacle Detection for Patrol Robot Using Bumblebee2 Stereo Vision System

2011 ◽  
Vol 48-49 ◽  
pp. 749-752 ◽  
Author(s):  
Xing Zhe Xie ◽  
Heng Wang ◽  
Qian You Luo
Keyword(s):  
Stereo Vision ◽  
Vision System ◽  
Ground Plane ◽  
Obstacle Detection ◽  
Consensus Algorithm ◽  
Analysis Method ◽  
Connected Component ◽  
Occupancy Grid ◽  
Stereo Vision System ◽  
Random Sample Consensus

This paper employs Bumblebee2 stereo vision system to detect the obstacles for patrol robot in substation environment. Firstly, with the selected points in the disparity image, the ground plane is calculated by the RANSAC (Random Sample Consensus) algorithm. And then, the local occupancy grid map is built for patrol robot, and the obstacles are detected through connected component analysis method. The actual test in substation environment verified the reliability of the system.

scholarly journals Hybrid Kalman Filter/Fuzzy Logic based Position Control of Autonomous Mobile Robot

10.5772/5789 ◽  
2005 ◽  
Vol 2 (3) ◽  
pp. 20 ◽  
Author(s):  
Rerngwut Choomuang ◽  
Nitin Afzulpurkar
Keyword(s):  
Fuzzy Logic ◽  
Kalman Filter ◽  
Mobile Robot ◽  
Position Control ◽  
Ground Plane ◽  
Systematic Errors ◽  
Obstacle Detection ◽  
Main Concern ◽  
Autonomous Mobile Robot ◽  
Wheel Slip

This paper describes position control of autonomous mobile robot using combination of Kalman filter and Fuzzy logic techniques. Both techniques have been used to fuse information from internal and external sensors to navigate a typical mobile robot in an unknown environment. An obstacle avoidance algorithm utilizing stereo vision technique has been implemented for obstacle detection. The odometry errors due to systematic-errors (such as unequal wheel diameter, the effect of the encoder resolution etc.) and/or non-systematic errors (ground plane, wheel-slip etc.) contribute to various motion control problems of the robot. During the robot moves, whether straight-line and/or arc, create the position and orientation errors which depend on systematic and/or non-systematic odometry errors. The main concern in most of the navigating systems is to achieve the real-time and robustness performances to precisely control the robot movements. The objective of this research is to improve the position and the orientation of robot motion. From the simulation and experiments, we prove that the proposed mobile robot moves from start position to goal position with greater accuracy avoiding obstacles.

Sign in / Sign up

Export Citation Format

Share Document