A Review: On using ACO Based Hybrid Algorithms for Path Planning of Multi-Mobile Robotics

Hamad, Ibrahim Ismael; Hasan, Mohammad Shahid

doi:10.3991/ijim.v14i18.16371

Cited by 10 publications

(4 citation statements)

References 46 publications

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“…As such, multilateral teleoperation and the fusion of multiple haptic transmission sources can also be explored. Furthermore, and given the need for the provisioning of low-latency and high-reliability communication, path optimization algorithms [42] can be utilized to optimize the communication pathways between different tactile nodes within the network and help improve the performance of tactile internet applications.…”

Section: Discussionmentioning

confidence: 99%

Emulation Framework for Haptic Data Transmission Using Real-Time Transport Protocol

Abdullah

Monnet

2023

Int. J. Onl. Eng.

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The Tactile Internet (TI) can be regarded as the next evolution in the world of communication. With its envisioned purpose and potential in shaping up the economy, industry and society, this paradigm aims to bring a new dimension to life by enabling humans to interact with machines remotely and in real-time with haptic and kinesthetic feedback. However, to translate this into reality, Tactile Internet will need to meet the stringent requirements of extremely low latency in conjunction with ultra-high reliability, availability, and security. This poses a challenge on the available communication systems to achieve a round-trip delay within 1 to 10 milliseconds time bound that enables the timely delivery of critical tactile and haptic sensations. This paper aims to evaluate the Real-Time Transport Protocol (RTP) through an emulation framework. It integrates containerization using Linux-based Docker Containers with NS-3 Network Simulator to conceptualize a haptic teleoperation system. The framework is then used to test the protocol’s feasibility for delivering texture haptic data between master and slave domains in accordance with the end-to-end delay requirements specified by IEEE 1918.1 standards. The results have shown that the timely provision of haptic data is achievable by obtaining an average round-trip delay of 17.8493 ms from the emulation experiment. As such, the results satisfy the expected IEEE 1918.1 standards constraints for medium-dynamic environment use cases.

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Section: Discussionmentioning

confidence: 99%

Emulation Framework for Haptic Data Transmission Using Real-Time Transport Protocol

Abdullah

Monnet

2023

Int. J. Onl. Eng.

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“…Marco Dorigo first proposed the ACO algorithm in his PhD thesis in 1992 [41]. He turned the behavior of ant colonies in terms of how they choose a certain path to seek and collect food into an artificial optimisation method for solving combinatorial issues [42]. The ACO method is a metaheuristic technique for quickly determining an approximate solution to complicated combinatorial optimisation issues [42].…”

Section: Ant Colony Optimizationmentioning

confidence: 99%

“…He turned the behavior of ant colonies in terms of how they choose a certain path to seek and collect food into an artificial optimisation method for solving combinatorial issues [42]. The ACO method is a metaheuristic technique for quickly determining an approximate solution to complicated combinatorial optimisation issues [42]. Ant behavior and their ability to locate the shortest path from their nest to a food source inspired the ACO algorithm.…”

Section: Ant Colony Optimizationmentioning

confidence: 99%

A review: On bio-inspired optimization methods for path planning of mobile robot

Hason

Al-Darraji

2023

IJICI

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In recent years, researchers have paid attention to algorithms inspired by nature where these algorithms have proven their efficiency in solving many optimization problems, especially in complex situations, due to their high precision, speed of optimization, simplicity of the techniques, and efficiency in agent cooperation. The primary issue in the field of autonomous mobile robots is navigation. An autonomous robot's navigation ability is one of its most crucial and distinctive features. There are four components of the autonomous robot navigation issue: vision, localization, cognition, and path planning. Many academics have used bio-inspired methods to solve navigation difficulties in mobile robots in recent years, including path planning where they considered the path planning problem as an optimization problem. Many novel path-planning methods have been created, and those using bio-inspired algorithms have received much attention. These algorithms have been shown to be useful in solving complex problems where the solution space isn't always adequately characterized and the problem necessitates solving complex mathematical models of live processes. More intricate optimization methods that transcend the constraints of classical procedures must be applied as the complexities of the optimization problem increase. This work contributes to presenting a group of algorithms inspired by nature that has been used to solve the problem of planning the path of mobile robots, and then making a comparison between these algorithms based on three factors (cost, time, and path length). Choosing an appropriate path-planning method contributes to ensuring safe and efficacious navigation from one point to another.

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“…It mimics the foraging behaviors of a swarm of bees to find food. ABC successfully used in many fields like Management of energy for mobile devices [2], [3] and for routing of Mobile Agents on IoT [4], [5]. The artificial bee colony is divided into three groups: employed, onlookers, and scouts' bees.…”

Section: Introductionmentioning

confidence: 99%

Systematic Review of Enhancement of Artificial Bee Colony Algorithm Using Ant Colony Pheromone

Alaidi

Chen

Leong

2021

Int. J. Interact. Mob. Technol.

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The artificial bee colony (ABC) is a well-studied algorithm developed to solve continuous function optimization problems by Karboga and Akay in 2009. ABC has been proven to be more effective than other biological-inspired algorithms with good exploration. However, ABC suffers from low exploitation and slow convergence in some cases. The ABC algorithm study has risen significantly over the past decade, with many researchers trying to improve ABC performance and apply it to solve problems. One method to enhance ABC is to borrow exploration technique from other algorithms. Researchers use pheromone, which is a technique used by Ant Colony optimization algorithm, to enhance ABC and addressed several aspects of using a pheromone to enhance the ABC. This systematic review aims to review and analysis articles about using pheromone to enhance ABC. Articles on related topics were systematically searched in four major databases namely Scopus, Web of Science, Association for Computing Machinery ACM and Google Scholar. To ensure that all research articles were considered the start date is not restrictions the search carry out till February 2021.Five articles were selected based on our inclusion and exclusion criteria for the systematic review. The results show that the use Pheromone to enhance ABC can increase the ABC exploitation ability and overcoming the late convergence. This paper also illustrates several potential pheromone using for future work.

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A Review: On using ACO Based Hybrid Algorithms for Path Planning of Multi-Mobile Robotics

Cited by 10 publications

References 46 publications

Emulation Framework for Haptic Data Transmission Using Real-Time Transport Protocol

Emulation Framework for Haptic Data Transmission Using Real-Time Transport Protocol

A review: On bio-inspired optimization methods for path planning of mobile robot

Systematic Review of Enhancement of Artificial Bee Colony Algorithm Using Ant Colony Pheromone

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