scholarly journals A Cognition Path Planning with a Nonlinear Controller Design for Wheeled Mobile Robot Based on an Intelligent Algorithm

2018 ◽  
Vol 25 (1) ◽  
pp. 64-83
Author(s):  
Ahmed S. Al-Araji ◽  
Attarid K. Ahmed ◽  
Khulood E. Dagher
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Controller Design ◽  
Optimal Path ◽  
Tracking Error ◽  
Pso Algorithm ◽  
Wheeled Mobile Robot ◽  
Torque Control ◽  
Nonlinear Controller ◽  
Reference Path

This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated reference path as well as it has obtained a perfect torque control action without spikes and no saturation torque state that leads to minimize the tracking error for the wheeled mobile robot.  

scholarly journals A COMPARATIVE STUDY FOR WHEELED MOBILE ROBOT PATH PLANNING BASED ON MODIFIED INTELLIGENT ALGORITHMS

2019 ◽  
Vol 19 (1) ◽  
pp. 60-74 ◽  
Author(s):  
Muna M AL -Nayar ◽  
Khulood E Dagher ◽  
Esraa A Hadi
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimization Technique ◽  
Pso Algorithm ◽  
Wheeled Mobile Robot ◽  
Robot Path Planning ◽  
Home Schools ◽  
The Social ◽  
Being There ◽  
Robot Path

From the time being, there are even instances for application of mobile robots in our lifelike in home, schools, hospitals, etc. The goal of this paper is to plan a path and minimizing thepath lengths with obstacles avoidance for a mobile robot in static environment. In this work wedepict the issue of off-line wheeled mobile robot (WMR) path planning, which best route forwheeled mobile robot from a start point to a target at a plane environment represented by 2-Dwork space. A modified optimization technique to solve the problem of path planning problemusing particle swarm optimization (PSO) method is given. PSO is a swarm intelligence basedstochastic optimization technique which imitate the social behavior of fish schooling or birdflocking, was applied to locate the optimum route for mobile robot so as to reach a target.Simulation results, which executed using MATLAB 2014 programming language, confirmedthat the suggested algorithm outperforms the standard version of PSO algorithm with the sameenvironment conditions by providing the shortest path for mobile robot.

Optimal path planning of a disinfection mobile robot against COVID-19 in a ROS-based research platform

2021 ◽  
Vol 16 (4) ◽  
pp. 405-417
Author(s):  
L. Banjanovic-Mehmedovic ◽  
I. Karabegovic ◽  
J. Jahic ◽  
M. Omercic
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Pso Algorithm ◽  
Optimal Path Planning ◽  
Localization And Mapping ◽  
Increasing Demand ◽  
Window Approach ◽  
Path Planner ◽  
Hardware Platforms ◽  
Reactive Collision

Due to COVID-19 pandemic, there is an increasing demand for mobile robots to substitute human in disinfection tasks. New generations of disinfection robots could be developed to navigate in high-risk, high-touch areas. Public spaces, such as airports, schools, malls, hospitals, workplaces and factories could benefit from robotic disinfection in terms of task accuracy, cost, and execution time. The aim of this work is to integrate and analyse the performance of Particle Swarm Optimization (PSO) algorithm, as global path planner, coupled with Dynamic Window Approach (DWA) for reactive collision avoidance using a ROS-based software prototyping tool. This paper introduces our solution – a SLAM (Simultaneous Localization and Mapping) and optimal path planning-based approach for performing autonomous indoor disinfection work. This ROS-based solution could be easily transferred to different hardware platforms to substitute human to conduct disinfection work in different real contaminated environments.

Development and analysis of DAYANI arc contour intelligent technique for navigation of two-wheeled mobile robot

2018 ◽  
Vol 45 (5) ◽  
pp. 688-702 ◽  
Author(s):  
Dayal R. Parhi ◽  
Animesh Chhotray
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Wheeled Mobile Robot ◽  
Weight Functions ◽  
Feasible Point ◽  
Content Type ◽  
Intelligent Technique ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Incremental Step

PurposeThis paper aims to generate an obstacle free real time optimal path in a cluttered environment for a two-wheeled mobile robot (TWMR).Design/methodology/approachThis TWMR resembles an inverted pendulum having an intermediate body mounted on a robotic mobile platform with two wheels driven by two DC motors separately. In this article, a novel motion planning strategy named as DAYANI arc contour intelligent technique has been proposed for navigation of the two-wheeled self-balancing robot in a global environment populated by obstacles. The developed new path planning algorithm evaluates the best next feasible point of motion considering five weight functions from an arc contour depending upon five separate navigational parameters.FindingsAuthenticity of the proposed navigational algorithm has been demonstrated by computing the path length and time taken through a series of simulations and experimental verifications and the average percentage of error is found to be about 6%.Practical implicationsThis robot dynamically stabilizes itself with taller configuration, can spin on the spot and rove along through obstacles with smaller footprints. This diversifies its areas of application to both indoor and outdoor environments especially with very narrow spaces, sharp turns and inclined surfaces where its multi-wheel counterparts feel difficult to perform.Originality/valueA new obstacle avoidance and path planning algorithm through incremental step advancement by evaluating the best next feasible point of motion has been established and verified through both experiment and simulation.

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