Model-Based Visual Navigation System For A Mobile Robot

1989 ◽  
Author(s):  
Juha Roning ◽  
Matti Pietikainen ◽  
Mikko Lindholm ◽  
Tapio Taipale
Keyword(s):  
Mobile Robot ◽  
Navigation System ◽  
Visual Navigation ◽  
Model Based

Visual Navigation System for a Mobile Robot

2005 ◽  
Author(s):  
K. Onoguchi ◽  
M. Watanabe ◽  
Y. Okamoto ◽  
H. Asada
Keyword(s):  
Mobile Robot ◽  
Navigation System ◽  
Visual Navigation

scholarly journals Indoor Vision/INS Integrated Mobile Robot Navigation Using Multimodel-Based Multifrequency Kalman Filter

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yuan Xu ◽  
Tongqian Liu ◽  
Bin Sun ◽  
Yong Zhang ◽  
Siamak Khatibi ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Mobile Robot ◽  
Navigation System ◽  
Robot Navigation ◽  
Visual Navigation ◽  
Mobile Robot Navigation ◽  
Integrated Navigation ◽  
Position Information ◽  
Integrated Navigation System ◽  
Navigation Method

In order to further improve positioning accuracy, this paper proposes an indoor vision/INS integrated mobile robot navigation method using multimodel-based multifrequency Kalman filter. Firstly, to overcome the insufficient accuracy of visual data when a robot turns, a novel multimodel integrated scheme has been investigated for the mobile robots with Mecanum wheels which can make fixed point angled turns. Secondly, a multifrequency Kalman filter has been used to fuse the position information from both the inertial navigation system and the visual navigation system, which overcomes the problem that the filtering period of the integrated navigation system is too long. The proposed multimodel multifrequency Kalman filter gives the root mean square error (RMSE) of 0.0184 m in the direction of east and 0.0977 m in north, respectively. The RMSE of visual navigation system is 0.8925 m in the direction of east and 0.9539 m in north, respectively. Experimental results show that the proposed method is effective.

Indoor Navigation System of Omni-Directional Mobile Robot Based on Static Obstacles Avoidance

2020 ◽  
Vol 13 (1) ◽  
pp. 27
Author(s):  
Shaaban Ali Salman ◽  
Qais A. Khasawneh ◽  
Mohammad A. Jaradat ◽  
Mansour Y. Alramlawi
Keyword(s):  
Mobile Robot ◽  
Navigation System ◽  
Indoor Navigation ◽  
Indoor Navigation System

scholarly journals A novel navigation system for an autonomous mobile robot in an uncertain environment

Robotica ◽  
2021 ◽  
pp. 1-26
Author(s):  
Meng-Yuan Chen ◽  
Yong-Jian Wu ◽  
Hongmei He
Keyword(s):  
Mobile Robot ◽  
Navigation System ◽  
Autonomous Navigation ◽  
Clustering Algorithm ◽  
Modular Design ◽  
Optimal Path ◽  
Surrounding Environment ◽  
Computing Complexity ◽  
The Arts ◽  
Window Approach

Abstract In this paper, we developed a new navigation system, called ATCM, which detects obstacles in a sliding window with an adaptive threshold clustering algorithm, classifies the detected obstacles with a decision tree, heuristically predicts potential collision and finds optimal path with a simplified Morphin algorithm. This system has the merits of optimal free-collision path, small memory size and less computing complexity, compared with the state of the arts in robot navigation. The modular design of 6-steps navigation provides a holistic methodology to implement and verify the performance of a robot’s navigation system. The experiments on simulation and a physical robot for the eight scenarios demonstrate that the robot can effectively and efficiently avoid potential collisions with any static or dynamic obstacles in its surrounding environment. Compared with the particle swarm optimisation, the dynamic window approach and the traditional Morphin algorithm for the autonomous navigation of a mobile robot in a static environment, ATCM achieved the shortest path with higher efficiency.

scholarly journals Lower Limb Model Based Inertial Indoor Pedestrian Navigation System for Walking and Running

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Wanling Li ◽  
Zhi Xiong ◽  
Yiming Ding ◽  
Zhiguo Cao ◽  
Zhengchun Wang
Keyword(s):  
Navigation System ◽  
Lower Limb ◽  
Pedestrian Navigation ◽  
Model Based
Sign in / Sign up

Export Citation Format

Share Document