Intelligent Controller for Mobile Robot Based on Heuristic Rule Base Network

2011 ◽  
Vol 403-408 ◽  
pp. 4777-4785
Author(s):  
Singh Mukesh Kumar ◽  
Mishra Deepak Kumar ◽  
R. Parhi Dayal ◽  
Singh Mahendra Prasad
Keyword(s):  
Mobile Robot ◽  
Simple Algorithm ◽  
Human Perception ◽  
Dynamic Environments ◽  
Rule Base ◽  
Heuristic Rule ◽  
Optimum Trajectory ◽  
Intelligent Controller ◽  
Estimation Function ◽  
Base Network

This paper is related to the human perception based idea by using heuristic information for the navigation of mobile robots in cluttered dynamic environments which provides a general, robust, safe and optimized path. The heuristic rule base network consists of a simple algorithm which makes predefined estimation function very smaller. The estimation function should be adequately defined for desired movement in the environments. A navigation system using rule based technique that allows a mobile robot to travel in an environment about, which the robot has no prior knowledge. This heuristic rule is applied in conjunction with artificial neural network. The proposed intelligent controller provides an optimum trajectory which increases the effectiveness of a mobile robot. A series of simulations test has been conducted to show the effectiveness of the proposed algorithm.

scholarly journals Motion Planning and Control of an Omnidirectional Mobile Robot in Dynamic Environments

Robotics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 48
Author(s):  
Mahmood Reza Azizi ◽  
Alireza Rastegarpanah ◽  
Rustam Stolkin
Keyword(s):  
Mobile Robot ◽  
Collision Avoidance ◽  
Motion Control ◽  
Equations Of Motion ◽  
Dynamic Environments ◽  
Discrete State ◽  
Omnidirectional Mobile Robot ◽  
Planning And Control ◽  
Avoidance Strategy ◽  
And Performance

Motion control in dynamic environments is one of the most important problems in using mobile robots in collaboration with humans and other robots. In this paper, the motion control of a four-Mecanum-wheeled omnidirectional mobile robot (OMR) in dynamic environments is studied. The robot’s differential equations of motion are extracted using Kane’s method and converted to discrete state space form. A nonlinear model predictive control (NMPC) strategy is designed based on the derived mathematical model to stabilize the robot in desired positions and orientations. As a main contribution of this work, the velocity obstacles (VO) approach is reformulated to be introduced in the NMPC system to avoid the robot from collision with moving and fixed obstacles online. Considering the robot’s physical restrictions, the parameters and functions used in the designed control system and collision avoidance strategy are determined through stability and performance analysis and some criteria are established for calculating the best values of these parameters. The effectiveness of the proposed controller and collision avoidance strategy is evaluated through a series of computer simulations. The simulation results show that the proposed strategy is efficient in stabilizing the robot in the desired configuration and in avoiding collision with obstacles, even in narrow spaces and with complicated arrangements of obstacles.

Human-centered X–Y–T space path planning for mobile robot in dynamic environments

2015 ◽  
Vol 66 ◽  
pp. 18-26 ◽  
Author(s):  
Ippei Nishitani ◽  
Tetsuya Matsumura ◽  
Mayumi Ozawa ◽  
Ayanori Yorozu ◽  
Masaki Takahashi
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Dynamic Environments
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