Line map construction using a mobile robot with a sonar sensor

2006 ◽  
Author(s):  
M.A. Kareem Jaradat ◽  
R. Langari
Keyword(s):  
Mobile Robot ◽  
Map Construction ◽  
Sonar Sensor

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.

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.

CORRIDOR-SCENE CLASSIFYING METHODS FOR MOBILE ROBOT BASED ON MULTI-SONAR-SENSOR INFORMATION FUSION

2007 ◽  
Vol 04 (01) ◽  
pp. 15-26 ◽  
Author(s):  
XIUQING WANG ◽  
ZENG-GUANG HOU ◽  
LONG CHENG ◽  
MIN TAN ◽  
FEI ZHU
Keyword(s):  
Principal Component Analysis ◽  
Mobile Robot ◽  
Principal Component ◽  
Component Analysis ◽  
Experimental Results ◽  
Scene Analysis ◽  
Kernel Principal Component Analysis ◽  
Kernel Pca ◽  
Sonar Sensor ◽  
Pca Method

The ability of cognition and recognition for complex environment is very important for a real autonomous robot. A new scene analysis method using kernel principal component analysis (kernel-PCA) for mobile robot based on multi-sonar-ranger data fusion is put forward. The principle of classification by principal component analysis (PCA), kernel-PCA, and the BP neural network (NN) approach to extract the eigenvectors which have the largest k eigenvalues are introduced briefly. Next the details of PCA, kernel-PCA and the BP NN method applied in the corridor scene analysis and classification for the mobile robots based on sonar data are discussed and the experimental results of those methods are given. In addition, a corridor-scene-classifier based on BP NN is discussed. The experimental results using PCA, kernel-PCA and the methods based on BP neural networks (NNs) are compared and the robustness of those methods are also analyzed. Such conclusions are drawn: in corridor scene classification, the kernel-PCA method has advantage over the ordinary PCA, and the approaches based on BP NNs can also get satisfactory results. The robustness of kernel-PCA is better than that of the methods based on BP NNs.

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.

Localization and Path Planning for an Autonomous Mobile Robot Equipped with Sonar Sensor

2015 ◽  
Vol 772 ◽  
pp. 494-499 ◽  
Author(s):  
Corina Monica Pop ◽  
Gheorghe Leonte Mogan ◽  
Mihail Neagu
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Mobile Robotics ◽  
Planning Process ◽  
Autonomous Mobile Robot ◽  
Sonar Sensors ◽  
Sonar Sensor ◽  
Simulation Results ◽  
Effectiveness And Efficiency ◽  
Global Trajectory

In the field of mobile robotics, the process of robot localization and global trajectory planning in robot operating scenes, that are completely or partially known, represents one of the main issues that are essential for providing the desired robot functionality. This paper introduces the basic elements of path planning for an autonomous mobile robot equipped with sonar sensors, operating in a static environment. The path planning process is initially performed by using a known map. Next, the sonar sensors are used to localize the robot, based on obstacle avoidance techniques. The effectiveness and efficiency of the algorithm proposed in this paper is demonstrated by the simulation results.

Removal of sonar wave interference in multi-robot system for the efficient SLAM by randomized triggering time technique

2020 ◽  
Vol 17 (4) ◽  
pp. 535-542
Author(s):  
Ravinder Singh ◽  
Akshay Katyal ◽  
Mukesh Kumar ◽  
Kirti Singh ◽  
Deepak Bhola
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Cross Talk ◽  
Autonomous Navigation ◽  
Content Type ◽  
Occupancy Grid ◽  
Grid Map ◽  
Wave Interference ◽  
Sonar Sensor ◽  
Occupancy Grid Map

Purpose Sonar sensor-based mobile robot mapping is an efficient and low cost technique for the application such as localization, autonomous navigation, SLAM and path planning. In multi-robots system, numbers of sonar sensors are used and the sound waves from sonar are interacting with the sound wave of other sonar causes wave interference. Because of wave interference, the generated sonar grid maps get distorted which resulted in decreasing the reliability of mobile robot’s navigation in the generated grid maps. This research study focus in removing the effect of wave interfaces in the sonar mapping to achieve robust navigation of mobile robot. Design/methodology/approach The wrong perception (occupancy grid map) of the environment due to cross talk/wave interference is eliminated by randomized the triggering time of sonar by varying the delay/sleep time of each sonar sensor. A software-based approach randomized triggering technique (RTT) is design in laboratory virtual instrument engineering workbench (LabVIEW) that randomized the triggering time of the sonar sensor to eliminate the effect of wave interference/cross talk when multiple sonar are placed in face-forward directions. Findings To check the reliability of the RTT technique, various real-world experiments are perform and it is experimentally obtained that 64.8% improvement in terms of probabilities in the generated occupancy grid map has been attained when compared with the conventional approaches. Originality/value This proposed RTT technique maybe implementing for SLAM, reliable autonomous navigation, optimal path planning, efficient robotics vision, consistent multi-robotic system, etc.

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
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