Optimal path planning of mobile robot using the hybrid cuckoo–bat algorithm in assorted environment

Murali, Gunji Bala; Deepak, B. B. V. L.; M.B.L., Saraswathi; Mogili, Umamaheswara Rao

doi:10.1108/ijius-07-2018-0021

Cited by 15 publications

(10 citation statements)

References 12 publications

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“…In robotics, several problems have been solved successfully by BA include tracking system [ 62 , 63 ], mobile robot [ 118 , 217 ], path planning and UAV path planning [ 178 , 182 , 305 , 342 ], and robotics [ 166 , 232 , 250 , 283 , 289 ]. These applications are demonstrated in Fig.…”

Section: Applications Of Bat-inspired Algorithmmentioning

confidence: 99%

Recent advances of bat-inspired algorithm, its versions and applications

Alyasseri

Alomari

Al-Betar

et al. 2022

Neural Comput & Applic

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Bat-inspired algorithm (BA) is a robust swarm intelligence algorithm that finds success in many problem domains. The ecosystem of bat animals inspires the main idea of BA. This review paper scanned and analysed the state-of-the-art researches investigated using BA from 2017 to 2021. BA has very impressive characteristics such as its easy-to-use, simple in concepts, flexible and adaptable, consistent, and sound and complete. It has strong operators that incorporate the natural selection principle through survival-of-the-fittest rule within the intensification step attracted by local-best solution. Initially, the growth of the recent solid works published in Scopus indexed articles is summarized in terms of the number of BA-based Journal articles published per year, citations, top authors, work with BA, top institutions, and top countries. After that, the different versions of BA are highlighted to be in line with the complex nature of optimization problems such as binary, modified, hybridized, and multiobjective BA. The successful applications of BA are reviewed and summarized, such as electrical and power system, wireless and network system, environment and materials engineering, classification and clustering, structural and mechanical engineering, feature selection, image and signal processing, robotics, medical and healthcare, scheduling domain, and many others. The critical analysis of the limitations and shortcomings of BA is also mentioned. The open-source codes of BA code are given to build a wealthy BA review. Finally, the BA review is concluded, and the possible future directions for upcoming developments are suggested such as utilizing BA to serve in dynamic, robust, multiobjective, large-scaled optimization as well as improve BA performance by utilizing structure population, tuning parameters, memetic strategy, and selection mechanisms. The reader of this review will determine the best domains and applications used by BA and can justify their BA-related contributions.

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Section: Applications Of Bat-inspired Algorithmmentioning

confidence: 99%

Recent advances of bat-inspired algorithm, its versions and applications

Alyasseri

Alomari

Al-Betar

et al. 2022

Neural Comput & Applic

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“…A hybrid mobile robot path planning algorithm was proposed in [3] that combines two nature-inspired meta-heuristics, based on cuckoo and bat behaviors, i.e., the parasitic behavior of cuckoos and the echolocation behavior of bats. The algorithm was further improved and tested using a real robot in [21]. The test results indicated that, although accuracy has been improved, the two algorithms require tuning parameters that might affect their performance in a complex environment.…”

Section: Literature Reviewmentioning

confidence: 99%

Tide-Inspired Path Planning Algorithm for Autonomous Vehicles

et al. 2021

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With the extensive developments in autonomous vehicles (AV) and the increase of interest in artificial intelligence (AI), path planning is becoming a focal area of research. However, path planning is an NP-hard problem and its execution time and complexity are major concerns when searching for optimal solutions. Thus, the optimal trade-off between the shortest path and computing resources must be found. This paper introduces a path planning algorithm, tide path planning (TPP), which is inspired by the natural tide phenomenon. The idea of the gravitational attraction between the Earth and the Moon is adopted to avoid searching blocked routes and to find a shortest path. Benchmarking the performance of the proposed algorithm against rival path planning algorithms, such as A*, breadth-first search (BFS), Dijkstra, and genetic algorithms (GA), revealed that the proposed TPP algorithm succeeded in finding a shortest path while visiting the least number of cells and showed the fastest execution time under different settings of environment size and obstacle ratios.

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“…CSA is built on three basic rules: 1 each cuckoo lays one egg at a time in a randomly selected nest; 2 the best nests with quality eggs will be passed on to future generations; and 3 the number of nests in CSA is fixed and the eggs left will be found with a probability between 0 and 1 by the host bird. If the host bird finds the cuckoo egg, it will either get rid of the egg or leave the existing nest to establish a new nest Gunji et al, 2019) CSA uses a combination of local and global random walk. p a indicates the discovery rate of alien nests, which is shown in the following formula that controls this combination.…”

Section: Cuckoo Search Algorithmmentioning

confidence: 99%

Modelling of fuel flow-rate of commercial aircraft for the climbing flight using cuckoo search algorithm

Oruç

Baklacıoğlu

2020

AEAT

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Purpose The purpose of this study is to create a new fuel flow rate model adopting cuckoo search algorithm (CSA) for the climbing phase of the flight. Design/methodology/approach Using the real flight data records (FDRs) of B737-800 passenger aircraft, a new fuel flow rate model for the climbing phase of the flight was developed by incorporating CSA. In the model, fuel flow rate is given as a function of altitude and true airspeed. The aim is to create a model that yields results that are closest to the real fuel flow rate values obtained from flight data records. Various error analysis methods were used to test the accuracy of the obtained values. Finally, the effect of change of some CSA parameters on the model was investigated. Findings It was observed that the derived model is able to predict real fuel flow rate values with high accuracy. It has been deduced that increasing the number of nest (n) and discovery rate of alien nests (pa) values of CSA parameters to a certain value gradually decreases the model’s accuracy. Practical implications This model is considered to be useful in air traffic management decision support systems, simulation applications, aircraft trajectory prediction models and aircraft performance modelling studies because of the high accuracy accomplished by the CSA model. Originality/value The originality of this study is the development of a new fuel flow rate model using CSA as a first attempt in the literature. The use of real flight data is important for the originality and reliability of the model.

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Optimal path planning of mobile robot using the hybrid cuckoo–bat algorithm in assorted environment

Cited by 15 publications

References 12 publications

Recent advances of bat-inspired algorithm, its versions and applications

Recent advances of bat-inspired algorithm, its versions and applications

Tide-Inspired Path Planning Algorithm for Autonomous Vehicles

Modelling of fuel flow-rate of commercial aircraft for the climbing flight using cuckoo search algorithm

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