scholarly journals Obstacle Avoidance and Target Tracking by Two Wheeled Differential Drive Mobile Robot Using ANFIS in Static and Dynamic Environment

2021 ◽  
pp. 337-348
Author(s):  
Dhruv Patel ◽  
Kelly Cohen
Keyword(s):  
Mobile Robot ◽  
Target Tracking ◽  
Obstacle Avoidance ◽  
Dynamic Environment ◽  
Differential Drive

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.

A Stereo Vision Based Target Tracking and Obstacle Avoidance

2009 ◽  
Vol 419-420 ◽  
pp. 565-568 ◽  
Author(s):  
Chao Ching Ho
Keyword(s):  
Mobile Robot ◽  
Target Tracking ◽  
Obstacle Avoidance ◽  
Visual Tracking ◽  
Stereo Vision ◽  
Vision System ◽  
Tracking System ◽  
Video Data ◽  
Corner Detection ◽  
Harris Corner

Designing a visual tracking system to track an object is a complex task because a large amount of video data must be transmitted and processed in real time. In this study, a stereo vision system is used to acquire the 3D positions of the target, tracking can be achieved by applying the CAMSHIFT algorithm, then apply the fuzzy reasoning control to steer the mobile robot to follow the selected target and avoid the in-path obstacles. The adopted obstacle avoidance component is based on the Harris corner detection and the binocular stereo imaging, which performs the correspondence calculation. Therefore a depth map is created and showing the relative 3D distances of the detected substantial features to the robot, which provides the information of the in-path obstacles in front of the wheeled mobile robot. The designed visual tracking and servo system is less sensitive to lighting influences and thus performs more efficiently. Experimental results showed that the mobile robot vision system successfully finished the target-following task by avoiding obstacles.

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 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.

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