Application of cellular automata and type-2 fuzzy logic to dynamic vehicle path planning

Huang, Chenn‐Jung; Wang, Yu-Wu; Chen, Heng-Ming; Tsai, Han-Wen; Jian, Jui-Jiun; Cheng, Ai-Lin; Liao, Jia-Jian

doi:10.1016/j.asoc.2014.02.023

Cited by 9 publications

(6 citation statements)

References 28 publications

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“…As a future work, we plan to deploy and assess the proposed approach in more complex scenarios where also cleaning failures and social navigation issues are considered. To this end, routing algorithms [49,50] and human action recognition methods [51][52][53][54] will be investigated and integrated. We are also interested in learning methods to adapt the dimension and the strategies of the robot team with respect to the heatmap status in order to reduce power consumption and maintenance costs, while preserving the quality of the sanitization.…”

Section: Discussionmentioning

confidence: 99%

A multi-robot deep Q-learning framework for priority-based sanitization of railway stations

et al. 2023

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Sanitizing railway stations is a relevant issue, primarily due to the recent evolution of the Covid-19 pandemic. In this work, we propose a multi-robot approach to sanitize railway stations based on a distributed Deep Q-Learning technique. The proposed framework relies on anonymous data from existing WiFi networks to dynamically estimate crowded areas within the station and to develop a heatmap of prioritized areas to be sanitized. Such heatmap is then provided to a team of cleaning robots - each endowed with a robot-specific convolutional neural network - that learn how to effectively cooperate and sanitize the station’s areas according to the associated priorities. The proposed approach is evaluated in a realistic simulation scenario provided by the Italian largest railways station: Roma Termini. In this setting, we consider different case studies to assess how the approach scales with the number of robots and how the trained system performs with a real dataset retrieved from a one-day data recording of the station’s WiFi network.

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Section: Discussionmentioning

confidence: 99%

A multi-robot deep Q-learning framework for priority-based sanitization of railway stations

et al. 2023

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“…In practical applications, no matter what kind of inspection task, the multimobile robot system needs to decompose and allocate tasks first; then, each robot separately formulates a reasonable inspection path. e commonly used path planning methods mainly include artificial potential field method, A-star algorithm, and fuzzy logic, which, however, have certain defects for different practical problems [28]. In order to accomplish various kinds of inspection tasks, the widely used BENN method will be introduced in the next part, and the IBENN algorithm will be proposed in Section 3.…”

Section: All-area Inspectionmentioning

confidence: 99%

“…(30,10), and the positions of the 6 inspection points are A 1(11,27), A 2(29,28),A 3 (3, 18), A 4(16,15), A 5 (13, 3), and A 6…”

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confidence: 99%

Design and Collaborative Operation of Multimobile Inspection Robots in Smart Microgrids

Chen

Wang

2021

Complexity

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This paper investigates the substation inspection problems of multimobile robots for large power stations in smart microgrids. Most multirobot inspection robots generally face the challenge of path planning, while the current widely used biological excitation neural network (BENN) methods often have the defect of the neuronal active field near boundaries and obstacles. To end this, we propose an improved biological excitation neural network (IBENN) method for path planning based on a detailed architecture and ontology framework, through which the single-point inspection, multipoint inspection, and full-area inspection tasks of substations in smart microgrids can be well completed. Simulation results show that the designed IBENN-based multirobot collaboration inspection (MRCI) system can effectively shorten the path as well as the number of turns and then show better performance than most existing results when implementing various substation inspection tasks.

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“…Later on, Nguyen et al 2015 apply GIS as a tool to generate an evolutionary planning multi-criteria model better than using the conventional traditional planning ways, as GIS analyzed the LSA problems in both attribute and geographical spaces. The last approach is called cellular automata which consist of set cells in a one or multi-dimensional criteria, as these cells are considered spatial cells so they are involved in simulating urban development (Huang et al 2014). Malczewski 2006 suggested integrating GIS as a powerful tool for applying cellular automata approach in LSA field.…”

Section: Multi-criteria Decision Making Techniques Integrated With Gimentioning

confidence: 99%

Land Suitability Analysis as Multi Criteria Decision Making to Support the Egyptian Urban Development

Sayed

2018

Resourceedings

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Sustainability in urban development is considered as a main concrete stone that effect directly the quality of life for its users. Land Suitability Analysis (LSA) using GIS as a multi criteria support tool reveals the best alternatives for the suitability of sustainable land development. Urban planners working under the umbrella of sustainability using recent technology should contribute their work directly to LSA. This paper aims to develop a new technique to be used by planner to reach best alternative for five main urban sectors (agriculture, Industry, Trade, Tourism, & Residential) using GIS as a multi criteria decision support tool (MCDS), accordingly choosing best city location will be accurately and analyzed upon LSA studies. LSA and MCDS are going to be applied on one survey unit map called Monof along Cairo – Alexandria Road. Results showed that different alternatives could be applied on the area of interest, and all of them are sustainable, but choosing the best deepened on the priority of querying the development sector. The paper suggests a pilot method for land development planning and choosing best city location that would be a guide for the governmental planning organization to support in taking right and analyzed planning decisions.

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Application of cellular automata and type-2 fuzzy logic to dynamic vehicle path planning

Cited by 9 publications

References 28 publications

A multi-robot deep Q-learning framework for priority-based sanitization of railway stations

A multi-robot deep Q-learning framework for priority-based sanitization of railway stations

Design and Collaborative Operation of Multimobile Inspection Robots in Smart Microgrids

Land Suitability Analysis as Multi Criteria Decision Making to Support the Egyptian Urban Development

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