scholarly journals Cash Collection Model of Electric Power Business Office Based on Computer Algorithm

2022 ◽  
Vol 2146 (1) ◽  
pp. 012023
Author(s):  
Binghua Guo ◽  
Nan Guo
Keyword(s):  
Mobile Robot ◽  
Medical Treatment ◽  
Electric Power ◽  
Obstacle Avoidance ◽  
Dynamic Environment ◽  
Dynamic Environments ◽  
Main Trend ◽  
Intelligent Robot ◽  
Treatment Service ◽  
Intelligent Algorithms

Abstract With the continuous development of intelligent algorithms, mobile robot (hereinafter referred to as MR) technology is gradually mature, which has been widely used in a variety of industries, such as industry, agriculture, medical treatment, service and so on. With the improvement of intelligent level, people have higher and higher requirements for MRs, which requires MRs to constantly adapt to different environments, especially dynamic environments. In the dynamic environment, obstacle avoidance technology has become the focus of intelligent robot research, which needs to continuously develop a variety of algorithms. By combining a variety of algorithms, we can realize obstacle avoidance and PP (hereinafter referred to as PP) of MR, which can realize obstacle avoidance more efficiently, in real time and intelligently. Multi algorithm fusion of MR has become the main trend of obstacle avoidance in the future, which will realize PP and optimization. Firstly, this paper analyzes the differences between traditional algorithms and intelligent algorithms. Then, the kinematics model and PP algorithm of MR are analyzed. Finally, the simulation is carried out.

scholarly journals Modeling and Analysis of the Obstacle-Avoidance Strategies for a Mobile Robot in a Dynamic Environment

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Rui Wang ◽  
Ming Wang ◽  
Yong Guan ◽  
Xiaojuan Li
Keyword(s):  
Energy Consumption ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Obstacle Avoidance ◽  
Decision Process ◽  
Dynamic Environment ◽  
Formal Models ◽  
Modeling And Analysis ◽  
Avoidance Strategies ◽  
Markov Decision

Obstacle avoidance is a key performance of mobile robots. However, its experimental verification is rather difficult, due to the probabilistic behaviors of both the robots and the obstacles. This paper presents the Markov Decision Process based probabilistic formal models for three obstacle-avoidance strategies of a mobile robot in an uncertain dynamic environment. The models are employed to make analyses in PRISM, and the correctness of the analysis results is verified by MATLAB simulations. Finally, the minimum time and the energy consumption are determined by further analyses in PRISM, which prove to be useful in finding the optimal strategy. The present work provides a foundation for the probabilistic formal verification of more complicated obstacle-avoidance strategies.

Research on Mobile Robot SLAM in Dynamic Environment

2011 ◽  
Vol 130-134 ◽  
pp. 232-238
Author(s):  
Bai Fan Chen ◽  
Zi Xing Cai
Keyword(s):  
Mobile Robot ◽  
Experimental Test ◽  
Data Association ◽  
Dynamic Environment ◽  
Dynamic Environments ◽  
Target Model ◽  
Dynamic Objects ◽  
Objects Detection

A SLAMiDE（SLAM in Dynamic Environments) system is designed and realized in the paper, which supplies a holistic framework and a series of implementation methods for mobile robot SLAM in dynamic environments. A uniform target model is proposed in SLAMiDE system. The dynamic targets and static targets and the mobile robot pose are estimated simultaneously, by synthesized the research of the data association and dynamic targets detection and static SLAM based on local maps. Finally, the results of the experimental test prove that the SLAMiDE system can realize dynamic objects detection and mapping and location correctly.

A Mobile Robot Obstacle Avoidance Using Fuzzy Logic and Model Predictive Control

2014 ◽  
Vol 548-549 ◽  
pp. 922-927
Author(s):  
Bayanjargal Baasandorj ◽  
Aamir Reyaz ◽  
Park Joung Ho ◽  
Cha Wang Cheol ◽  
Deok Jin Lee ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Model Predictive Control ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Predictive Control ◽  
Real Life ◽  
Dynamic Environment ◽  
Logic Control ◽  
Microwave Sensor ◽  
Very High

This paper presents a method of solving the problem of mobile robot Obstacle avoidance and path planning in an unknown dynamic environment. A linear model of the two-wheeled nonholonomic robot controlled using Model predictive control controller. For obstacle avoidance Fuzzy logic control is used. The ultrasonic sensors are used for positioning and identifying an obstacle. The proposed method is successfully tested in simulations. Obstacle avoiding technique is very useful in real life, this technique can also use as a vision belt of blind people by changing the IR sensor by a kinetic sensor ,which is on type of microwave sensor whose sensing range is very high and the output of this sensor vary in according to the object position changes.

scholarly journals Fuzzy Logic Navigation and Obstacle Avoidance by a Mobile Robot in an Unknown Dynamic Environment

10.5772/54427 ◽  
2013 ◽  
Vol 10 (1) ◽  
pp. 37 ◽  
Author(s):  
Mohammed Faisal ◽  
Ramdane Hedjar ◽  
Mansour Al Sulaiman ◽  
Khalid Al-Mutib
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Dynamic Environment

Vision-Based Moving Obstacle Avoidance for Cable-Driven Parallel Robots Using Improved Rapidly Exploring Random Tree

2020 ◽  
Author(s):  
Jiajun Xu ◽  
Kyoung-su Park
Keyword(s):  
Obstacle Avoidance ◽  
Dynamic Environment ◽  
Dynamic Environments ◽  
Parallel Robots ◽  
Random Tree ◽  
Experimental Setup ◽  
Bounding Box ◽  
Vision Algorithm ◽  
Moving Obstacle

Abstract In this study, the improved vision-based rapidly exploring random tree (RRT) algorithm is proposed to address moving obstacle avoidance for cable-driven parallel robots (CDPRs). The improved RRT algorithm is goal-biased with dynamic stepsize makes it possible to implement in dynamic environments. For the implementation of algorithm on CDPRs, the improved RRT considers various collisions caused by the cable. The axis-aligned bounding box (AABB) algorithm is used for the fast re-planning during the RRT process. Additionally, the improved RRT algorithm premeditates the complex constrains include force feasible workspace (FFW) and the segment-to-segment angle. The related simulation is given in order to illustrate the algorithm. An experimental setup is also presented using the drone as a moving obstacle and the Faster-RCNN vision algorithm to obtain the coordinate of the drone. The experiment result shows that the proposed algorithm can apply in CDPRs with the dynamic environment validly.

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