scholarly journals A Visual Navigation Control Method of Substation Inspection Robot

Author(s):  
Liqiang ZHONG ◽  
Shaosheng FAN ◽  
Shaohai ZHANG ◽  
Di YANG
Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4181 ◽  
Author(s):  
Chun-Hui Lin ◽  
Shyh-Hau Wang ◽  
Cheng-Jian Lin

In this paper, a navigation method is proposed for cooperative load-carrying mobile robots. The behavior mode manager is used efficaciously in the navigation control method to switch between two behavior modes, wall-following mode (WFM) and goal-oriented mode (GOM), according to various environmental conditions. Additionally, an interval type-2 neural fuzzy controller based on dynamic group artificial bee colony (DGABC) is proposed in this paper. Reinforcement learning was used to develop the WFM adaptively. First, a single robot is trained to learn the WFM. Then, this control method is implemented for cooperative load-carrying mobile robots. In WFM learning, the proposed DGABC performs better than the original artificial bee colony algorithm and other improved algorithms. Furthermore, the results of cooperative load-carrying navigation control tests demonstrate that the proposed cooperative load-carrying method and the navigation method can enable the robots to carry the task item to the goal and complete the navigation mission efficiently.


Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 946 ◽  
Author(s):  
Tianfan Zhang ◽  
Weiwen Zhou ◽  
Fei Meng ◽  
Zhe Li

In view of the future lack of human resources due to the aging of the population, the automatic, Intelligent Mechatronic Systems (IMSs) and Intelligent Transportation Systems (ITSs) have broad application prospects. However, complex application scenarios and limited open design resources make designing highly efficient ITS systems still a challenging task. In this paper, the optimal load factor solving solution is established. By converting the three user requirements including working distance, time and load into load-related factors, the optimal result can be obtained among system complexity, efficiency and system energy consumption. A specialized visual navigation and motion control system has been proposed to simplify the path planning, navigation and motion control processes and to be accurately calculated in advance, thereby further improving the efficiency of the ITS system. The validity of the efficiency calculation formula and navigation control method proposed in this paper is verified. Under optimal conditions, the actual working mileage is expected to be 99.7%, and the energy consumption is 83.5% of the expected value, which provides sufficient redundancy for the system. In addition, the individual ITS reaches the rated operating efficiency of 95.86%; in other words, one ITS has twice the ability of a single worker. This proves the accuracy and efficiency of the designed ITS system.


Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 298 ◽  
Author(s):  
Jyun-Yu Jhang ◽  
Cheng-Jian Lin ◽  
Kuu-Young Young

This study provides an effective cooperative carrying and navigation control method for mobile robots in an unknown environment. The manager mode switches between two behavioral control modes—wall-following mode (WFM) and toward-goal mode (TGM)—based on the relationship between the mobile robot and the unknown environment. An interval type-2 fuzzy neural controller (IT2FNC) based on a dynamic group differential evolution (DGDE) is proposed to realize the carrying control and WFM control for mobile robots. The proposed DGDE uses a hybrid method that involves a group concept and an improved differential evolution to overcome the drawbacks of the traditional differential evolution algorithm. A reinforcement learning strategy was adopted to develop an adaptive WFM control and achieve cooperative carrying control for mobile robots. The experimental results demonstrated that the proposed DGDE is superior to other algorithms at using WFM control. Moreover, the experimental results demonstrate that the proposed method can complete the task of cooperative carrying, and can realize navigation control to enable the robot to reach the target location.


2015 ◽  
Vol 727-728 ◽  
pp. 736-739
Author(s):  
Ming Ming Bian ◽  
Jin Lan Zhang

A model for a mobile inspection robot is introduced. Based on human driving behavior, a fuzzy control method for mobile robot path tracking is proposed. Angular velocity controller is established by distance error and angle error. Angular velocity is controlled to implement path tracking of the wheeled mobile robot. Experimental results show that the effectiveness of the inspection robot controller is good and it is effective.


2012 ◽  
Vol 11 (9) ◽  
pp. 1219-1226 ◽  
Author(s):  
Juing-Shian Chiou ◽  
Ming-Yuan Shieh ◽  
Kun-Hung Li

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