Enhancements of PECOS Embedded Real-Time Component Model for Autonomous Mobile Robot Application

2006 ◽  
Author(s):  
D.N.A. Jawawi ◽  
S. Deris ◽  
R. Mamat
Keyword(s):  
Mobile Robot ◽  
Real Time ◽  
Component Model ◽  
Autonomous Mobile Robot ◽  
Time Component

ASYNCHRONOUS PRODUCTION SYSTEM FOR CONTROL OF AN AUTONOMOUS MOBILE ROBOT IN REAL-TIME ENVIRONMENT

1992 ◽  
Vol 6 (4) ◽  
pp. 485-509 ◽  
Author(s):  
S. S. IYENGAR ◽  
A. SABHARWAL ◽  
F. G. PIN ◽  
C. R. WEISBIN
Keyword(s):  
Mobile Robot ◽  
Real Time ◽  
Production System ◽  
Autonomous Mobile Robot

Research on Navigation and Obstacle Avoidance Algorithm for Autonomous Mobile Robot in Narrow Area

2011 ◽  
Vol 464 ◽  
pp. 204-207
Author(s):  
Huan Xun Li ◽  
Jun Jie Shen ◽  
Shuai Guo
Keyword(s):  
Mobile Robot ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Extraction Method ◽  
Field Method ◽  
Autonomous Mobile Robot ◽  
Environment Modeling ◽  
Feature Extraction Method ◽  
Potential Field Method ◽  
Narrow Area

In order to improve the accuracy and security when autonomous mobile robot moves in narrow area, a real-time navigation and obstacle avoidance algorithm is put forward. The feature extraction method is used to search for the path points, and the angle potential field method is used to search for the target angle. Based on the two methods more accurate environment modeling and navigation for mobile robot in narrow area is realized. The algorithm has been used successfully in the household robot, and the experiment results show it’s accurate and real-time.

scholarly journals A Real-Time Action Search for Autonomous Mobile Robot.

1999 ◽  
Vol 17 (4) ◽  
pp. 503-512 ◽  
Author(s):  
Kae Fujisawa ◽  
Soichiro Hayakawa ◽  
Takeshi Aoki ◽  
Tatsuya Suzuki ◽  
Shigeru Okuma
Keyword(s):  
Mobile Robot ◽  
Real Time ◽  
Autonomous Mobile Robot ◽  
Action Search

Development of Autonomous Mobile Robot for Obstacle Avoidance

1993 ◽  
Vol 5 (5) ◽  
pp. 481-486 ◽  
Author(s):  
Masafumi Uchida ◽  
◽  
Syuichi Yokoyama ◽  
Hideto Ide ◽  
Keyword(s):  
Mobile Robot ◽  
Motion Planning ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Potential Method ◽  
Working Environment ◽  
Planning Problem ◽  
Autonomous Mobile Robot ◽  
The Real

The potential method is superior for solving the problem of motion planning; however, it must address the problem of the real-time generation of potential field. Obstacle avoidance is a motion planning problem. In a previous study, we investigated the real-time generation of potential field. Based on parallel processing with element group, we proposed the system by Sensory Point Moving (SPM) method. As a result of computer simulation, it was confirmed that the SPM method is effective for generating an obstacle avoidance path in 2-D and a more complex working environment like a 3-D one. In this paper, we discuss the development of autonomous mobile robot for obstacle avoidance based on the SPM method.

Autonomous Mobile Robot Searching for Persons with Specific Clothing on Urban Walkway

2017 ◽  
Vol 29 (4) ◽  
pp. 649-659 ◽  
Author(s):  
Ryohsuke Mitsudome ◽  
◽  
Hisashi Date ◽  
Azumi Suzuki ◽  
Takashi Tsubouchi ◽  
...  
Keyword(s):  
Object Recognition ◽  
Mobile Robot ◽  
Real Time ◽  
Real World ◽  
Laser Scanner ◽  
High Accuracy ◽  
Autonomous Mobile Robot ◽  
World Environment

In order for a robot to provide service in a real world environment, it has to navigate safely and recognize the surroundings. We have participated in Tsukuba Challenge to develop a robot with robust navigation and accurate object recognition capabilities. To achieve navigation, we have introduced the ROS packages, and the robot was able to navigate without major collisions throughout the challenge. For object recognition, we used both a laser scanner and camera to recognize a person in specific clothing, in real time and with high accuracy. In this paper, we evaluate the accuracy of recognition and discuss how it can be improved.

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