Energy Efficient Path Planning for Indoor Wheeled Mobile Robots

2020 ◽  
Author(s):  
Jing Liu ◽  
Zhaojun Li ◽  
Li-Ping He ◽  
Wanying Shi
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Energy Efficient ◽  
Wheeled Mobile Robots

scholarly journals A new optimization-driven path planning method with probabilistic completeness for wheeled mobile robots

2019 ◽  
Vol 52 (5-6) ◽  
pp. 317-325 ◽  
Author(s):  
Bo You ◽  
Zhi Li ◽  
Liang Ding ◽  
Haibo Gao ◽  
Jiazhong Xu
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Mobile Robots ◽  
Energy Efficient ◽  
Planning Process ◽  
Planning Method ◽  
Projection Algorithm ◽  
Wheeled Mobile Robots ◽  
Active Set ◽  
Weak Minima

Wheeled mobile robots are widely utilized for environment-exploring tasks both on earth and in space. As a basis for global path planning tasks for wheeled mobile robots, in this study we propose a method for establishing an energy-based cost map. Then, we utilize an improved dual covariant Hamiltonian optimization for motion planning method, to perform point-to-region path planning in energy-based maps. The method is capable of efficiently handling high-dimensional path planning tasks with non-convex cost functions through applying a robust active set algorithm, that is, non-monotone gradient projection algorithm. To solve the problem that the path planning process is locked in weak minima or non-convergence, we propose a randomized variant of the improved dual covariant Hamiltonian optimization for motion planning based on simulated annealing and Hamiltonian Monte Carlo methods. The results of simulations demonstrate that the final paths generated can be time efficient, energy efficient and smooth. And the probabilistic completeness of the method is guaranteed.

scholarly journals Grey Wolf Optimizer-Based Approaches to Path Planning and Fuzzy Logic-based Tracking Control for Mobile Robots

2020 ◽  
Vol 15 (3) ◽  
Author(s):  
Radu-Emil Precup ◽  
Emil-Ioan Voisan ◽  
Emil M. Petriu ◽  
Marius L. Tomescu ◽  
Radu-Codrut David ◽  
...  
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Tracking Control ◽  
Fuzzy Controller ◽  
Optimization Problems ◽  
Cost Effective ◽  
Grey Wolf Optimizer ◽  
Reference Trajectory ◽  
Grey Wolf ◽  
Wheeled Mobile Robots

This paper proposes two applications of Grey Wolf Optimizer (GWO) algorithms to a path planning (PaPl) problem and a Proportional-Integral (PI)-fuzzy controller tuning problem. Both optimization problems solved by GWO algorithms are explained in detail. An off-line GWO-based PaPl approach for Nonholonomic Wheeled Mobile Robots (NWMRs) in static environments is proposed. Once the PaPl problem is solved resulting in the reference trajectory of the robots, the paper also suggests a GWO-based approach to tune cost-effective PI-fuzzy controllers in tracking control problem for NWMRs. The experimental results are demonstrated through simple multiagent settings conducted on the nRobotic platform developed at the Politehnica University of Timisoara, Romania, and they prove both the effectiveness of the two GWO-based approaches and major performance improvement.

Path Planning and Path Tracking of Industrial Mobile Robots

2010 ◽  
pp. 84-124
Author(s):  
Sašo Blažic ◽  
El-Hadi Guechi ◽  
Jimmy Lauber ◽  
Michel Dambrine ◽  
Gregor Klancar
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Global Stability ◽  
Main Part ◽  
Path Tracking ◽  
Trajectory Design ◽  
Wheeled Mobile Robots ◽  
Physical Limitations ◽  
Takagi Sugeno ◽  
Reference Trajectories

The purpose of this chapter is to give a quick state of the art and to propose some new approaches in the area of path planning and path tracking for the differentially driven wheeled mobile robots. The main part of the chapter is devoted to the methods that ensure stable tracking of the prescribed reference trajectories. Of particular importance are the approaches that result in global stability of the tracking, e.g. Lyapunov-based control and parallel distributed Takagi-Sugeno fuzzy control. The effects of discrete measurements and delay on the control performance are also analysed. The second part of the chapter is devoted to path planning or trajectory design. Here, physical limitations of the robot and obstacle avoidance are treated.

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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