Disparity Image Plane Segmentation Based Obstacle Map Construction for Mobile Robot

ROBOT ◽  
2010 ◽  
Vol 32 (2) ◽  
pp. 171-178
Author(s):  
Xinkun SONG ◽  
Wanmi CHEN ◽  
Yulin XU ◽  
Lei ZHANG
Keyword(s):  
Mobile Robot ◽  
Image Plane ◽  
Map Construction

Omni-Directional Vision System for Mobile Robot Using Structured Lights

2013 ◽  
Vol 288 ◽  
pp. 114-120 ◽  
Author(s):  
Yue Zhang ◽  
Yuan Li ◽  
Qing Lin Wang
Keyword(s):  
Mobile Robot ◽  
Vision System ◽  
Image Plane ◽  
Environmental Information ◽  
Mobile Robot Navigation ◽  
Distance Information ◽  
Laser Illumination ◽  
Map Construction ◽  
Laser Plane ◽  
Structured Light Vision

Vision system can obtain rich environmental information, and vision is one of the most important sensing methods for mobile robot navigation and positioning. An omni-directional vision system using laser illumination is presented. The system can obtain the distance information of the obstacles around the mobile robot by only one image. The principle of the vision system is expounded; the mapping relationship between the image plane and the laser plane is given based on the analysis of the system model. The system benefits from the advantages of the omni-directional vision and the structured light vision, such as large ranged environmental information, high precision and robustness, etc. Experimental results of measurement and map construction verify the vision system.

scholarly journals Rapid Relocation Method for Mobile Robot Based on Improved ORB-SLAM2 Algorithm

2019 ◽  
Vol 11 (2) ◽  
pp. 149 ◽  
Author(s):  
Guanci Yang ◽  
Zhanjie Chen ◽  
Yang Li ◽  
Zhidong Su
Keyword(s):  
Mobile Robot ◽  
Dynamic Environment ◽  
Original System ◽  
Tracking Accuracy ◽  
Vocabulary Size ◽  
Map Construction ◽  
Speed Tracking ◽  
Start Up ◽  
C Programming ◽  
Robot Platform

In order to realize fast real-time positioning after a mobile robot starts, this paper proposes an improved ORB-SLAM2 algorithm. Firstly, we proposed a binary vocabulary storage method and vocabulary training algorithm based on an improved Oriented FAST and Rotated BRIEF (ORB) operator to reduce the vocabulary size and improve the loading speed of the vocabulary and tracking accuracy. Secondly, we proposed an offline map construction algorithm based on the map element and keyframe database; then, we designed a fast reposition method of the mobile robot based on the offline map. Finally, we presented an offline visualization method for map elements and mapping trajectories. In order to check the performance of the algorithm in this paper, we built a mobile robot platform based on the EAI-B1 mobile chassis, and we implemented the rapid relocation method of the mobile robot based on improved ORB SLAM2 algorithm by using C++ programming language. The experimental results showed that the improved ORB SLAM2 system outperforms the original system regarding start-up speed, tracking and positioning accuracy, and human–computer interaction. The improved system was able to build and load offline maps, as well as perform rapid relocation and global positioning tracking. In addition, our experiment also shows that the improved system is robust against a dynamic environment.

scholarly journals Adaptive Visually Servoed Tracking Control for Wheeled Mobile Robot with Uncertain Model Parameters in Complex Environment

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Fujie Wang ◽  
Yi Qin ◽  
Fang Guo ◽  
Bin Ren ◽  
John T. W. Yeow
Keyword(s):  
Mobile Robot ◽  
Visual Servoing ◽  
Dynamic Control ◽  
Kinematic Model ◽  
Image Plane ◽  
Adaptive Controller ◽  
Wheeled Mobile Robot ◽  
General Situation ◽  
Model Parameters ◽  
Complex Environment

This paper investigates the stabilization and trajectory tracking problem of wheeled mobile robot with a ceiling-mounted camera in complex environment. First, an adaptive visual servoing controller is proposed based on the uncalibrated kinematic model due to the complex operation environment. Then, an adaptive controller is derived to provide a solution of uncertain dynamic control for a wheeled mobile robot subject to parametric uncertainties. Furthermore, the proposed controllers can be applied to a more general situation where the parallelism requirement between the image plane and operation plane is no more needed. The overparameterization of regressor matrices is avoided by exploring the structure of the camera-robot system, and thus, the computational complexity of the controller can be simplified. The Lyapunov method is employed to testify the stability of a closed-loop system. Finally, simulation results are presented to demonstrate the performance of the suggested control.

Multipath Bayesian Map Construction Model from Sonar Data

Robotica ◽  
1996 ◽  
Vol 14 (5) ◽  
pp. 527-540 ◽  
Author(s):  
Jong Hwan Lim ◽  
Dong Woo Chof†
Keyword(s):  
Mobile Robot ◽  
Real World ◽  
Probabilistic Approach ◽  
Bayesian Reasoning ◽  
Occupancy Probability ◽  
Map Construction ◽  
Sonar Sensor ◽  
A Cell ◽  
Construction Model ◽  
Wrong Interpretation

SUMMARYA new model for the construction of a sonar map in a specular environment has been developed and implemented. In a real world, where most of the object surfaces are specular ones, a sonar sensor surfers from a multipath effect which results in a wrong interpretation of an object's location. To reduce this effect and hence to construct a reliable map of a robot's surroundings, a probabilistic approach based on Bayesian reasoning is adopted to both evaluation of object orientations and estimation of an occupancy probability of a cell by an object. The usefulness of this approach is illustrated with the results produced by our mobile robot equipped with ultrasonic sensors.

Navigation of a mobile robot by locally optimal trajectories

Robotica ◽  
1999 ◽  
Vol 17 (5) ◽  
pp. 553-562 ◽  
Author(s):  
Kokou Djath ◽  
Ali Siadet ◽  
Michel Dufaut ◽  
Didier Wolf
Keyword(s):  
Mobile Robot ◽  
Shortest Path ◽  
Laser Scanner ◽  
Navigation Algorithm ◽  
Map Construction ◽  
Unstructured Environment ◽  
Environment Perception ◽  
Simple Equations ◽  
Holonomic Mobile Robot ◽  
Local Map

This paper proposes a navigation system for a non-holonomic mobile robot. The navigation is based on a “look and move” approach. The aim is to define intermediate points called sub-goals through which the robot must pass. This algorithm is particularly suitable for navigation in an unknown environment and obstacle avoidance. Between two successive sub-goals, a shortest path planning solution is adopted. We have adopted the “Dubins' car” because of the environment perception sensor, a 180° laser scanner. In order to minimize the calculation time, the theoretical results of shortest path are approximated by simple equations. The navigation algorithm proposed can be used either in a structured or unstructured environment. In this context the local map construction is based on the segmentation of a structured environment; so for an unstructured environment, a suitable algorithm must be used instead.

Position Uncertainty Reduction of Mobile Robot Based on DINDs in Intelligent Space

2008 ◽  
Vol 12 (6) ◽  
pp. 488-493
Author(s):  
TaeSeok Jin ◽  
◽  
Hideki Hashimoto ◽  
Keyword(s):  
Mobile Robot ◽  
A Priori ◽  
Dead Reckoning ◽  
Constraint Equation ◽  
Image Plane ◽  
Moving Object ◽  
Camera Model ◽  
Intelligent Space ◽  
Point Object ◽  
Position Data

This paper proposes a localization of mobile robot using the images by distributed intelligent networked devices (DINDs) in intelligent space (ISpace). This scheme combines data from the observed position using dead-reckoning sensors and the estimated position using images of moving object, such as those of a walking human, used to determine the moving location of a mobile robot. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Using the a-priori known path of a moving object and a perspective camera model, the geometric constraint equations that represent the relation between image frame coordinates of a moving object and the estimated position of the robot are derived. The proposed approach is applied for a mobile robot in ISpace to show the reduction of uncertainty in the determining of the location of the mobile robot.

Robust ground plane region detection using multiple visual cues for obstacle avoidance of a mobile robot

Robotica ◽  
2014 ◽  
Vol 33 (2) ◽  
pp. 436-450 ◽  
Author(s):  
Chia-How Lin ◽  
Kai-Tai Song
Keyword(s):  
Image Processing ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Visual Cues ◽  
Feature Matching ◽  
Imaging System ◽  
Ground Plane ◽  
Image Plane ◽  
Monocular Camera ◽  
Camera View

SUMMARYThis paper presents a vision-based obstacle avoidance design using a monocular camera onboard a mobile robot. A novel image processing procedure is developed to estimate the distance between the robot and obstacles based-on inverse perspective transformation (IPT) in an image plane. A robust image processing solution is proposed to detect and segment a drivable ground area within the camera view. The proposed method integrates robust feature matching with adaptive color segmentation for plane estimation and tracking to cope with variations in illumination and camera view. After IPT and ground region segmentation, distance measurement results are obtained similar to those of a laser range finder for mobile robot obstacle avoidance and navigation. The merit of this algorithm is that the mobile robot can have the capacity of path finding and obstacle avoidance by using a single monocular camera. Practical experimental results on a wheeled mobile robot show that the proposed imaging system successfully obtains distances of surrounding objects for reactive navigation in an indoor environment.

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