Optimal motion planning for minimizing energy consumption of wheeled mobile robots

2017 ◽  
Author(s):  
R. Datouo ◽  
F. Biya Motto ◽  
B. Essimbi Zobo ◽  
A. Melingui ◽  
I. Bensekrane ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Motion Planning ◽  
Mobile Robots ◽  
Optimal Motion ◽  
Wheeled Mobile Robots ◽  
Optimal Motion Planning

EB-RRT: Optimal Motion Planning for Mobile Robots

2020 ◽  
Vol 17 (4) ◽  
pp. 2063-2073 ◽  
Author(s):  
Jiankun Wang ◽  
Max Q.-H. Meng ◽  
Oussama Khatib
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Optimal Motion ◽  
Optimal Motion Planning

Optimal Motion Planning Approach for Mobile Robot Navigation Problem

2015 ◽  
Vol 799-800 ◽  
pp. 1078-1082
Author(s):  
Bashra Kadhim Oleiwi ◽  
Hubert Roth ◽  
Bahaa I. Kazem
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Spline Interpolation ◽  
Optimal Solution ◽  
Mobile Robot Navigation ◽  
Optimal Motion ◽  
Navigation Problem ◽  
Modified Genetic Algorithm ◽  
Planning Approach ◽  
Optimal Motion Planning

In this study, modified genetic algorithm (MGA) and A* search method (A*) is proposed for optimal motion planning of mobile robots. MGA utilizes the classical search and modified A* to establish a sub-optimal collision-free path as initial solution in simple and complex static environment. The enhancements for the proposed approach are presented in initialization stage and enhanced operators. Five objective functions are used to minimize traveling length, time, smoothness, security and trajectory and to reduce the energy consumption for mobile robots by using Cubic Spline interpolation curve fitting for optimal planned path. The purpose of this study is to evaluate the proposed approach performance by taking into consideration the effect of changing the number of iteration (it) and the size of population (pop) on its performance index. The simulation results show the effectiveness of proposed approach in governing the robot’s movements successfully from start to goal point after avoiding all obstacles its way in all tested environment. In addition, the results indicate that the proposed approach can find the optimal solution efficiently in a single run. This approach has been carried out by GUI using a popular engineering programming language, MATLAB.

Risk-DTRRT-Based Optimal Motion Planning Algorithm for Mobile Robots

2019 ◽  
Vol 16 (3) ◽  
pp. 1271-1288 ◽  
Author(s):  
Wenzheng Chi ◽  
Chaoqun Wang ◽  
Jiankun Wang ◽  
Max Q.-H. Meng
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Optimal Motion ◽  
Optimal Motion Planning ◽  
Planning Algorithm

scholarly journals An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3517
Author(s):  
Mohammad Mohammadpour ◽  
Lotfi Zeghmi ◽  
Sousso Kelouwani ◽  
Marc-André Gaudreau ◽  
Ali Amamou ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Motion Planning ◽  
Mobile Robots ◽  
Energy Efficient ◽  
Wheeled Mobile Robots ◽  
Production Chain ◽  
Planning Stage ◽  
Material Transportation ◽  
Global Energy Consumption

In recent years, the use of electric Autonomous Wheeled Mobile Robots (AWMRs) has dramatically increased in transport of the production chain. Generally, AWMRs must operate for several hours on a single battery charge. Since the energy density of the battery is limited, energy efficiency becomes a key element in improving material transportation performance during the manufacturing process. However, energy consumption is influenced by the navigation stages, because the type of motion necessary for the AWMR to perform during a mission is totally defined by these stages. Therefore, this paper analyzes methods of energy efficiency that have been studied recently for AWMR navigation stages. The selected publications are classified into planning and motion control categories in order to identify research gaps. Unlike other similar studies, this work focuses on these methods with respect to their implications for the energy consumption of AWMRs. In addition, by using an industrial Self-Guided Vehicle (SGV), we illustrate the direct influence of the motion planning stage on global energy consumption by means of several simulations and experiments. The results indicate that the reaction of the SGV in response to unforeseen obstacles can affect the amount of energy consumed. Hence, energy constraints must be considered when developing the motion planning of AWMRs.

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