A review of methodologies for path planning and optimization of mobile robots

Sahoo, S. C.; Choudhury, B. B.

doi:10.5937/jouproman2301122s

Cited by 7 publications

(2 citation statements)

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“…Blockchain technology is gaining popularity due to its ability to improve transparency and trust in supply chain activities. Blockchain maintains an immutable ledger of all transactions, making record manipulation or tampering nearly impossible [38]. This technique is especially useful for assuring the authenticity of items and the integrity of supply chain information [39].…”

Section: Industry 40 Technologies In Supply Chain Managementmentioning

confidence: 99%

A Review of Digital Transformation and Industry 4.0 in Supply Chain Management for Small and Medium-sized Enterprises

Sahoo,

Goswami,

Sarkar

et al. 2023

Spec. Eng. Man. Sci.

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The introduction of Industry 4.0, which includes a suite of advanced technologies such as the Internet of Things (IoT), big data analytics, artificial intelligence, and cyber-physical systems, has substantially altered supply chain dynamics in recent years. Digital Transformation and Industry 4.0 have emerged as pivotal paradigms reshaping the landscape of supply chain management (SCM) across industries. This study begins with an overview of classic SCM concepts and progresses to the contemporary digital era. We investigate the fundamental principles of digital transformation in SCM, emphasizing its drivers and accompanying benefits. Following that, this study delves into small and medium-sized enterprises (SMEs) and discusses their integration inside SCM systems. Through a systematic analysis of literature and case studies, this review synthesizes key methodologies, challenges, and opportunities. It highlights the importance of tailored approaches encompassing technology adoption roadmaps, pilot projects, workforce upskilling, and cyber security measures. The review also underscores the critical role of future research in developing standardized frameworks and best practices to empower SMEs in harnessing the transformative potential of the digital age within their supply chains. This study also discusses digital transformation initiatives, their impact on SCM performance, and their role in improving supply chain resilience. Finally, this research article investigates the obstacles and barriers faced during digital transformation programs, as well as future trends and consequences for practitioners and researchers.

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Section: Industry 40 Technologies In Supply Chain Managementmentioning

confidence: 99%

A Review of Digital Transformation and Industry 4.0 in Supply Chain Management for Small and Medium-sized Enterprises

Sahoo,

Goswami,

Sarkar

et al. 2023

Spec. Eng. Man. Sci.

View full text Add to dashboard Cite

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“…For instance, the work in [24] proposes an hybrid PSO-SA algorithm for the optimization of AGV path planning. In [25], a comprehensive review of methodologies for path planning and optimization of mobile robots is provided. It includes not only the classic but state-of-the-art techniques such as artificial potential fields, GA, swarm intelligence, and machine learning-based methods.…”

Section: Related Workmentioning

confidence: 99%

Path Optimization Using Metaheuristic Techniques for a Surveillance Robot

Peñacoba,

Sierra-García,

Santos

et al. 2023

Applied Sciences

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This paper presents an innovative approach to optimize the trajectories of a robotic surveillance system, employing three different optimization methods: genetic algorithm (GA), particle swarm optimization (PSO), and pattern search (PS). The research addresses the challenge of efficiently planning routes for a LiDAR-equipped mobile robot to effectively cover target areas taking into account the capabilities and limitations of sensors and robots. The findings demonstrate the effectiveness of these trajectory optimization approaches, significantly improving detection efficiency and coverage of critical areas. Furthermore, it is observed that, among the three techniques, pattern search quickly obtains feasible solutions in environments with good initial trajectories. On the contrary, in cases where the initial trajectory is suboptimal or the environment is complex, PSO works better. For example, in the high complexity map evaluated, PSO achieves 86.7% spatial coverage, compared to 85% and 84% for PS and GA, respectively. On low- and medium-complexity maps, PS is 15.7 and 18 s faster in trajectory optimization than the second fastest algorithm, which is PSO in both cases. Furthermore, the fitness function of this proposal has been compared with that of previous works, obtaining better results.

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