MOSFLA-MRPP: Multi-Objective Shuffled Frog-Leaping Algorithm applied to Mobile Robot Path Planning

Hidalgo-Paniagua, Alejandro; Vega‐Rodríguez, Miguel A.; Ferruz, J.; Pavón, N.

doi:10.1016/j.engappai.2015.05.011

Cited by 63 publications

(22 citation statements)

References 21 publications

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“…And it was the first time that MOVNS [12] was proposed to deal with the path planning problem of mobile robots about the path safety, length, and smoothness. In addition, many other findings also made contributions to the related path planning problem [13][14][15].…”

Section: Introductionmentioning

confidence: 95%

An Improved Ant Colony Algorithm for Solving the Path Planning Problem of the Omnidirectional Mobile Vehicle

Zhao

Cheng

Chen

2016

Mathematical Problems in Engineering

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This paper presents an improved ant colony algorithm for the path planning of the omnidirectional mobile vehicle. The purpose of the improved ant colony algorithm is to design an appropriate route to connect the starting point and ending point of the environment with obstacles. Ant colony algorithm, which is used to solve the path planning problem, is improved according to the characteristics of the omnidirectional mobile vehicle. And in the improved algorithm, the nonuniform distribution of the initial pheromone and the selection strategy with direction play a very positive role in the path search. The coverage and updating strategy of pheromone is introduced to avoid repeated search reducing the effect of the number of ants on the performance of the algorithm. In addition, the pheromone evaporation coefficient is segmented and adjusted, which can effectively balance the convergence speed and search ability. Finally, this paper provides a theoretical basis for the improved ant colony algorithm by strict mathematical derivation, and some numerical simulations are also given to illustrate the effectiveness of the theoretical results.

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Section: Introductionmentioning

confidence: 95%

An Improved Ant Colony Algorithm for Solving the Path Planning Problem of the Omnidirectional Mobile Vehicle

Zhao

Cheng

Chen

2016

Mathematical Problems in Engineering

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“…Biologically inspired approaches take this idea of using three objectives to find feasible paths a step further. In Reference [6], Frog-Leaping algorithms are used, and, in Reference [21], fireflies behavior based algorithms are also used to solve path planning. In Reference [8], a MOVNS (Multi-Objective Variable Neighborhood Search) is used for the first time to solve the path planning for mobile robots; in this contribution, the smoothness factor is not simply used as a discriminant for coincident situations, but as another target on its own.…”

Section: Related Workmentioning

confidence: 99%

“…There are a lot of different algorithms that can be used and combined to achieve feasible path planning (e.g., those based on Evolutionary Computing (EC) or Artificial Intelligence (AI) techniques, among others); the election depends on what factors are relevant for the robot. Among these factors, three are usually considered to evaluate the trajectory of a robot: path length, path safety, and path smoothness [5,6].…”

Section: Introductionmentioning

confidence: 99%

Measuring Smoothness as a Factor for Efficient and Socially Accepted Robot Motion

Ruíz

Calderita

Hidalgo-Paniagua

et al. 2020

Sensors

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Social robots, designed to interact and assist people in social daily life scenarios, require adequate path planning algorithms to navigate autonomously through these environments. These algorithms have not only to find feasible paths but also to consider other requirements, such as optimizing energy consumption or making the robot behave in a socially accepted way. Path planning can be tuned according to a set of factors, being the most common path length, safety, and smoothness. This last factor may have a strong relation with energy consumption and social acceptability of produced motion, but this possible relation has never been deeply studied. The current paper focuses on performing a double analysis through two experiments. One of them analyzes energy consumption in a real robot for trajectories that use different smoothness factors. The other analyzes social acceptance for different smoothness factors by presenting different simulated situations to different people and collecting their impressions. The results of these experiments show that, in general terms, smoother paths decrease energy consumption and increase acceptability, as far as other key factors, such as distance to people, are fulfilled.

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“…This objective will help to reduce energy level as the mobile robot will navigate through the path with minimal turns in a straight way compared to a curvy path that's uses a lot more energy. Path smoothness can be measured through the following equation [4].…”

Section: Smoothnessmentioning

confidence: 99%

A Review on Autonomous Mobile Robot Path Planning Algorithms

Adzhar¹,

Yuhani²,

Ahmad³

2020

Adv. sci. technol. eng. syst. j.

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The emerging trend of modern industry automation requires intelligence to be embedded into mobile robot for ensuring optimal or near-optimal solutions to execute certain task. This yield to a lot of improvement and suggestions in many areas related to mobile robot such as path planning. The purpose of this paper is to review the mobile robots path planning problem, optimization criteria and various methodologies reported in the literature for global and local mobile robot path planning. In this paper, commonly use classical approaches such as cell decomposition (CD), roadmap approach (RA), artificial potential field (AFP), and heuristics approaches such as genetic algorithm (GA), particle swarm optimization (PSO) approach and ant colony optimization (ACO) method are considered. It is observed that when it comes to dynamic environment where most of the information are unknown to the mobile robots before starting, heuristics approaches are more popular and widely used compared to classical approaches since it can handle uncertainty, interact with objects and making quick decision. Finally, few suggestions for future research work in this field are addressed at the end of this paper.

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MOSFLA-MRPP: Multi-Objective Shuffled Frog-Leaping Algorithm applied to Mobile Robot Path Planning

Cited by 63 publications

References 21 publications

An Improved Ant Colony Algorithm for Solving the Path Planning Problem of the Omnidirectional Mobile Vehicle

An Improved Ant Colony Algorithm for Solving the Path Planning Problem of the Omnidirectional Mobile Vehicle

Measuring Smoothness as a Factor for Efficient and Socially Accepted Robot Motion

A Review on Autonomous Mobile Robot Path Planning Algorithms

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