scholarly journals Navigation Based on Vision and DGPS Information for Mobile Robots

1999 ◽  
Vol 11 (1) ◽  
pp. 45-53 ◽  
Author(s):  
Shinji Kotani ◽  
◽  
Ken’ichi Kaneko ◽  
Tatsuya Shinoda ◽  
Hideo Mori ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Navigation System ◽  
Vision System ◽  
Dead Reckoning ◽  
Initial Position ◽  
Map Matching ◽  
Autonomous Mobile Robot ◽  
Environmental Model ◽  
Position And Orientation

This paper describes a navigation system for an autonomous mobile robot in outdoors. The robot uses vision to detect landmarks and DGPS information to determine its initial position and orientation. The vision system detects landmarks in the environment by referring to an environmental model. As the robot moves, it calculates its position by conventional dead reckoning, and matches landmarks to the environmental model to reduce error in position calculation. The robot's initial position and orientation are calculated from coordinates of the first and second locations acquired by DGPS. Subsequent orientations and positions are derived by map matching. We implemented the system on a mobile robot, Harunobu 6. Experiments in real environments verified the effectiveness of our proposed navigation.

The KCLBOT: The Challenges of Stereo Vision for a Small Autonomous Mobile Robot

2012 ◽  
Author(s):  
Evangelos Georgiou ◽  
Jian S. Dai ◽  
Michael Luck
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Stereo Vision ◽  
Critical Path ◽  
Vision System ◽  
Autonomous Mobile Robots ◽  
Autonomous Mobile Robot ◽  
Sensory Data ◽  
King's College ◽  
Stereo Vision System

In small mobile robot research, autonomous platforms are severely constrained in navigation environments by the limitations of accurate sensory data to preform critical path planning, obstacle avoidance and self-localization tasks. The motivation for this work is to enable small autonomous mobile robots with a local stereo vision system that will provide an accurate reconstruction of a navigation environment for critical navigation tasks. This paper presents the KCLBOT, which was developed in King’s College London’s Centre for Robotic Research and is a small autonomous mobile robot with a stereo vision system.

Control of Autonomous Mobile Robot Using Map Matching with Optimized Search Range

2013 ◽  
Vol 133 (5) ◽  
pp. 502-509 ◽  
Author(s):  
Kouhei Komiya ◽  
Shunsuke Miyashita ◽  
Yutaka Maruoka ◽  
Yutaka Uchimura
Keyword(s):  
Mobile Robot ◽  
Map Matching ◽  
Autonomous Mobile Robot ◽  
Search Range

Navigation System for Olfactory Mobile Robot by Using Machine Vision System

2021 ◽  
Author(s):  
Gamma Aditya Rahardi ◽  
Khairul Anam ◽  
Ali Rizal Chaidir ◽  
Devita Ayu Larasati
Keyword(s):  
Machine Vision ◽  
Mobile Robot ◽  
Navigation System ◽  
Vision System ◽  
Machine Vision System

Expert Guided Autonomous Mobile Robot Learning

2011 ◽  
pp. 216-231
Author(s):  
Gintautas Narvydas ◽  
Vidas Raudonis ◽  
Rimvydas Simutis
Keyword(s):  
Control System ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Control Systems ◽  
Intelligent Control ◽  
Main Idea ◽  
Autonomous Mobile Robots ◽  
Autonomous Mobile Robot ◽  
Intelligent Control System ◽  
Objective Function Values

In the control of autonomous mobile robots there exist two types of control: global control and local control. The requirement to solve global and local tasks arises respectively. This chapter concentrates on local tasks and shows that robots can learn to cope with some local tasks within minutes. The main idea of the chapter is to show that, while creating intelligent control systems for autonomous mobile robots, the beginning is most important as we have to transfer as much as possible human knowledge and human expert-operator skills into the intelligent control system. Successful transfer ensures fast and good results. One of the most advanced techniques in robotics is an autonomous mobile robot on-line learning from the experts’ demonstrations. Further, the latter technique is briefly described in this chapter. As an example of local task the wall following is taken. The main goal of our experiment is to teach the autonomous mobile robot within 10 minutes to follow the wall of the maze as fast and as precisely as it is possible. This task also can be transformed to the obstacle circuit on the left or on the right. The main part of the suggested control system is a small Feed-Forward Artificial Neural Network. In some particular cases – critical situations – “If-Then” rules undertake the control, but our goal is to minimize possibility that these rules would start controlling the robot. The aim of the experiment is to implement the proposed technique on the real robot. This technique enables to reach desirable capabilities in control much faster than they would be reached using Evolutionary or Genetic Algorithms, or trying to create the control systems by hand using “If-Then” rules or Fuzzy Logic. In order to evaluate the quality of the intelligent control system to control an autonomous mobile robot we calculate objective function values and the percentage of the robot work loops when “If-Then” rules control the robot.

Control of Autonomous Mobile Robot Using Map Matching with Optimized Search Range

2014 ◽  
Vol 190 (4) ◽  
pp. 66-75 ◽  
Author(s):  
Kouhei Komiya ◽  
Shunsuke Miyashita ◽  
Yutaka Maruoka ◽  
YUTAKA Uchimura
Keyword(s):  
Mobile Robot ◽  
Map Matching ◽  
Autonomous Mobile Robot ◽  
Search Range

HOLONOMIC AND OMNIDIRECTIONAL LOCOMOTION SYSTEMS FOR WHEELED MOBILE ROBOTS: A REVIEW

2015 ◽  
Vol 77 (28) ◽  
Author(s):  
M. Juhairi Aziz Safar
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Degrees Of Freedom ◽  
Wheeled Mobile Robot ◽  
Arbitrary Direction ◽  
Current Position ◽  
Wheeled Mobile Robots ◽  
Future Improvement ◽  
Position And Orientation ◽  
Three Degrees Of Freedom

Holonomic and omnidirectional locomotion systems are best known for their capability to maneuver at any arbitrary direction regardless of their current position and orientation with a three degrees of freedom mobility. This paper summarizes the advancement of holonomic and omnidirectional locomotion systems for wheeled mobile robot applications and discuss the issues and challenges for future improvement.

Path-tracking controller design and implementation of a vision-based wheeled mobile robot

2009 ◽  
Vol 223 (6) ◽  
pp. 847-862 ◽  
Author(s):  
J-L Yang ◽  
D-T Su ◽  
Y-S Shiao ◽  
K-Y Chang
Keyword(s):  
Mobile Robot ◽  
Tracking Control ◽  
Intelligent System ◽  
Vision System ◽  
Dead Reckoning ◽  
Path Tracking ◽  
Wheeled Mobile Robot ◽  
Detection Methods ◽  
Control Laws ◽  
The Dead

This paper presents techniques for building system configuration, control architecture, and implementation of a vision-based wheeled mobile robot (WMR). The completed WMR has been built with the dead-reckoning method so as to determine the vehicle's velocity and posture by the numerical differentiation/integration over short travelling. The developed proportional-integral-derivative (PID) controllers show good transient performances; that is, the velocity of right and left wheels can track the commands quickly and correctly. Moreover, the path-tracking control laws have also been executed within the digital signal processor (DSP)-based controller in the WMR. The image-recognized system can obtain motion information at 15 frames/s by using the hybrid intelligent system (HIS) model, which is one of the well-known colour detection methods. The better performance a vision system has, the more successful the control laws design. The WMR obtains its posture from the dead-reckoning device together with the vision system. These subsystems are integrated, and the operators of the whole system are completed. This WMR system can be thought of as a platform for testing various tracking control laws and a signal-filtering method. To solve the problem of position/orientation tracking control of the WMR, two kinematical optimal non-linear predictive control laws are developed to manipulate the vehicle to follow the desired trajectories asymptotically. A Kalman filter scheme is used to reduce the bad effect of the imagine nose; thereby the accuracy of pose estimation can be improved. The experimental system is composed of a wireless RS232 modem, a DSP-based controller for the WMR, and a vision system with a host computer. A computation-effective and high-performance DSP-based controller is constructed for executing the developed sophisticated path-tracking laws. Finally, the simulation and experimental results show the feasibility and effectiveness of the proposed control laws.

Sign in / Sign up

Export Citation Format

Share Document