Planning Solution Research Articles

A Complete Coverage Path Planning Algorithm for Lawn Mowing Robots Based on Deep Reinforcement Learning

This paper introduces Re-DQN, a deep reinforcement learning-based algorithm for comprehensive coverage path planning in lawn mowing robots. In the fields of smart homes and agricultural automation, lawn mowing robots are rapidly gaining popularity to reduce the demand for manual labor. The algorithm introduces a new exploration mechanism, combined with an intrinsic reward function based on state novelty and a dynamic input structure, effectively enhancing the robot’s adaptability and path optimization capabilities in dynamic environments. In particular, Re-DQN improves the stability of the training process through a dynamic incentive layer and achieves more comprehensive area coverage and shorter planning times in high-dimensional continuous state spaces. Simulation results show that Re-DQN outperforms the other algorithms in terms of performance, convergence speed, and stability, making it a robust solution for comprehensive coverage path planning. Future work will focus on testing and optimizing Re-DQN in more complex environments and exploring its application in multi-robot systems to enhance collaboration and communication.

Unveiling the role of artificial intelligence applied to clear aligner therapy: A scoping review.

To conduct a scoping review on the application of artificial intelligence (AI) in clear aligner therapy and to assess the extent of AI integration and automation in orthodontic software currently available to orthodontists. A systematic electronic literature search was performed in the following databases: PubMed, Embase, Web of Science, Cochrane Library, and Scopus. Also, grey literature resources up to March 2024 were reviewed. English-language studies on potential AI applications for clear aligner therapy were included based on an independent evaluation by two reviewers. An assessment of the automation steps in orthodontic software available on the market up to March 2024 was also conducted. Out of 708 studies, 41 were included. Sixteen articles focused on tooth segmentation, four on registration of digital models, 13 on digital setup, and eight on remote monitoring. Moreover, 13 aligner software programs were identified and assessed for their level of automation. Only one software demonstrated complete automation of the steps involved in the orthodontic digital workflow. None of the 13 identified aligner software programs were evaluated in the 41 included studies. However, AI-based tooth segmentation achieved 98% accuracy, while AI effectively merged CBCT and IOS data, supported digital measurements, predicted treatment outcomes, and showed potential for remote monitoring. AI applications in clear aligner therapy are on the rise. This scoping review enables orthodontists to identify AI-based solutions in orthodontic planning and understand its implications, which can potentially enhance treatment efficiency, accuracy, and predictability.

Time-optimal trajectory planning for a six-degree-of-freedom manipulator: a method integrating RRT and chaotic PSO

This study proposes an innovative algorithm based on a hybrid optimization strategy, integrating the rapidly-exploring random tree (RRT) and an improved particle swarm optimization (PSO) method to address the time-optimal trajectory planning problem for six-degree-of-freedom robotic arms. The proposed approach emphasizes obstacle avoidance and motion smoothness. RRT is utilized within a dynamic three-dimensional environment to rapidly generate an initial collision-free path. Subsequently, improved PSO enhances global search performance by introducing a multi-source chaotic mapping-based population initialization strategy, dynamically adjusted inertia weights, and nonlinear learning factors. These enhancements effectively mitigate the limitations of traditional PSO methods, which are prone to premature convergence in complex optimization problems. Furthermore, the proposed 3-5-3 polynomial interpolation method significantly smooths the trajectory, reducing fluctuations in velocity and acceleration, and thereby improving the precision and energy efficiency of trajectory planning. Experimental results demonstrate that the proposed algorithm outperforms existing methods, such as the improved RRT and improved non-dominated sorting genetic algorithm, across multiple metrics. Notable achievements include a reduction of total motion time by approximately 21%, improved stability in robotic arm motion, and enhanced adaptability to dynamic environments. Particularly, the method achieves superior trajectory diversity and uniformity through joint optimization of multiple chaotic sources, overcoming the inherent limitations of single chaotic mappings. This research expands the application scenarios of RRT and PSO and provides a novel solution for intelligent control and real-time planning of high-degree-of-freedom robotic arms.

Adaptive Path Planning for Multi-UAV Systems in Dynamic 3D Environments: A Multi-Objective Framework

This study evaluates and compares the computational performance and practical applicability of advanced path planning algorithms for Unmanned Aerial Vehicles (UAVs) in dynamic and obstacle-rich environments. The Adaptive Multi-Objective Path Planning (AMOPP) framework is highlighted for its ability to balance multiple objectives, including path length, smoothness, collision avoidance, and real-time responsiveness. Through experimental analysis, AMOPP demonstrates superior performance, with a 15% reduction in path length compared to A*, achieving an average path length of 450 m. Its angular deviation of 8.0° ensures smoother trajectories than traditional methods like Genetic Algorithm and Particle Swarm Optimization (PSO). Moreover, AMOPP achieves a 0% collision rate across all simulations, surpassing heuristic-based methods like Cuckoo Search and Bee Colony Optimization, which exhibit higher collision rates. Real-time responsiveness is another key strength of AMOPP, with an average re-planning time of 0.75 s, significantly outperforming A* and RRT*. The computational complexities of each algorithm are analyzed, with AMOPP exhibiting a time complexity of O(k·n) and a space complexity of O(n), ensuring scalability and efficiency for large-scale operations. The study also presents a comprehensive qualitative and quantitative comparison of 14 algorithms using 3D visualizations, highlighting their strengths, limitations, and suitable application scenarios. By integrating weighted optimization with penalty-based strategies and spline interpolation, AMOPP provides a robust solution for UAV path planning, particularly in scenarios requiring smooth navigation and adaptive re-planning. This work establishes AMOPP as a promising framework for real-time, efficient, and safe UAV operations in dynamic environments.

Path planning for flexible needle based on both insertion mechanism kinematics and needle bending model.

Due to the limited operating space in the magnetic resonance (MR) environment, there is coupled motion in the insertion mechanism, which not only reduces the flexibility of the robot but also challenges the insertion path planning. Meanwhile, the path planning is also restricted by the bending rule of the flexible needle, thus the bending model of the needle is also essentially built. This paper proposes a path planner for the flexible needle based on both the coupled motion kinematics of the insertion robot and the bending model of the flexible needle. A kinematic analysis for the coupled motion of insertion robot is performed. And the bending model of flexible needle is established based on the needle-tissue interactions. The position and posture of the needle insertion at the entry point are obtained by the calculation of the target position and the analysis of the bending model. And the rotation or translation coordinates of each robot joint are calculated by the inverse kinematics of the insertion robot. Then the path planning based on the coupled kinematics and the bending model is realized. The insertion experiments were performed for each target of G1 and G2. The root mean square errors were 0.83 mm and 0.74 mm, and the maximum errors were 1.1 mm and 0.9 mm for G1 and G2, respectively. The experimental results show that the effectiveness and accuracy of the path planning can meet the requirements for a general minimally invasive surgery, so the proposed path planning algorithm is feasible. This study provides a new solution for the path planning of insertion robots for the minimally invasive surgery. This method can meet the insertion mechanism working within the limited operating space in the MR environment and has a high application value in future clinical medicine.

THERMAL REGIME OF THE TERRITORY OF THE COURTYARD OF A SECTIONAL RESIDENTIAL BUILDING DEPENDING ON ITS ORIENTATION

As average annual temperatures rise, residents of urban areas face the problem of significant heating of urban surfaces exposed to direct solar radiation. This process has a direct impact on the microclimate of both the entire urban area and individual adjacent territories. Shading of surfaces plays an important role in the thermoregulation of the living environment, which is confirmed by numerous studies on this topic. The introduction of natural methods to reduce the temperature regime is becoming relevant in terms of reducing heat stress and overall energy savings. In this paper, using the example of a sectional residential building of a U-shaped configuration with nine floors, we study the dependence of the percentage of shading and the amount of direct solar radiation entering the courtyard on its orientation to the cardinal points. The calculation was performed for a clear day on July 21, when the average monthly temperature was 24.6 °C according to the Boris Sreznevsky Central Geophysical Observatory. The calculation excluded the influence of surrounding buildings and green spaces. The amount of direct solar radiation per square meter of surface was calculated using the specialized Townscope program. Based on the results obtained, graphs of the total amount of direct solar radiation on the surface during the calculated period from 6:00 to 18:00 for different orientations of the courtyard space were built. The percentage of shading of the total area of the design surfaces was also calculated. Summary data tables were created for each design surface. The final results are of a recommendatory nature for design organizations in determining the optimal planning solution at the pre-design stage. Such an environmentally friendly approach, which is the basis of design work, can improve living conditions in urban settlements, reduce the negative impact on the environment, and make cities more resilient to climate change.

THEORETICAL AND METHODOLOGICAL APPROACHES TO PROCESSES OF DEVELOPMENT OF URBAN SPACES: ZONING AND PLANNING

In the modern context of rapid urbanization and city growth, the issue of effective zoning and urban space planning is extremely relevant. Sustainable approaches to urban infrastructure development require the integration of environmental, social, and economic aspects. Current urban planning methods often fail to meet the requirements of sustainable development due to insufficient integration of new technologies, inadequate community involvement, and a lack of effective coordination between public and private institutions. The aim of the study is to develop theoretical and methodological approaches to urban space development through the improvement of zoning and planning methods. The objectives include analyzing international experience, assessing current planning methods, and developing recommendations for their adaptation to national conditions. The object of the study is the urban spaces of modern cities. The subject of the study is the approaches to zoning and urban space planning. The study employed methods of analysis, synthesis, systematic approach, comparative analysis, and expert assessments. These methodologies provided a comprehensive understanding of the strengths and limitations of existing urban planning practices. Key methodological aspects of effective zoning and urban planning, considering ecological, social, and technological challenges, have been identified, ensuring a balanced approach to development. The research emphasized the importance of integrating smart technologies and sustainable practices to enhance urban functionality. Additionally, recommendations for their application in Ukraine have been developed, highlighting the need for policy adjustments and strategic partnerships to implement modern urban planning solutions effectively.The research found that the adaptation of international experience, particularly the use of mixed zoning and smart technologies, will promote the sustainable development of urban spaces in Ukraine. Future research may focus on developing practical recommendations for the implementation of modern methods in Ukraine's urban planning policy.

APPROACHES TO OPTIMIZING DESIGN SOLUTIONS OF ARCHITECTURAL OBJECTS AND COMPLEXES UNDER THE INFLUENCE OF INNOVATIVE TECHNOLOGIES

It has been established that in solving the problem of increasing the efficiency of urban environment development, a special place belongs to design, in which scientific and technical achievements are implemented. They determine the technical and economic level of production. The article is devoted to the study of approaches to optimizing design solutions of architectural objects. The concept of “optimization of design solutions” is defined. It is determined that the optimization of architectural and urban planning solutions is one of the most important areas of architectural activity. It determines the main approaches to improving the quality of the living environment of the population, considering social, ideological, functional, structural and technical, economic, urban planning and compositional requirements. It is determined that design searches for the creation of innovative buildings that ensure high quality of the urban environment should be carried out systematically using computer modelling of objects. The main characteristics and influence of innovative technologies on the process of optimizing design solutions of architectural objects and complexes have been identified. It has been established that the strategic direction of qualitative transformations of buildings and structures in the urban environment is the improvement of their material and spatial characteristics, including functional, ecological and aesthetic components, as well as the modernization of infrastructure and information and communication systems. Modern approaches to optimizing design solutions of architectural objects of various functional purposes have been identified. It is determined that the procedure for selecting the best project option happens considering the specifics of the task of comprehensive assessment of design solutions. This considers the number and technical and economic content of the criteria, the multivariate nature of architectural, construction, organizational and technological solutions. Its implementation is based on establishing the hierarchical significance of the criteria and the range of their limitations depending on the tasks and material and financial capabilities of the customer. It is important to narrow down the set of options after going through them at each hierarchical level and select effective solutions that meet the given limitations. Perspective trends have been identified in the field of implementing solutions for the optimal use of exterior spaces of various functional purposes. Such perspective trends are aimed at humanizing the living, working and recreational environment of a person, considering regional, national, natural and climatic and other features, environmental, technical, sanitary and hygienic and aesthetic requirements. They provide for the rational use of territorial and other architectural and urban resources, protection of the population and reduction of damage from possible manifestations of dangerous man-made and geological natural disasters, preservation of valuable architectural and urban heritage, development of national and cultural traditions in architecture and urban planning.

Genetic algorithm-based path planning of quadrotor UAVs on a 3D environment

Abstract In this article, a genetic algorithm (GA) is proposed as a solution for the path planning of unmanned aerial vehicles (UAVs) in 3D, both static and dynamic environments. In most cases, genetic algorithms are utilised for optimisation in offline applications; however, this work proposes an approach that performs real-time path planning with the capability to avoid dynamic obstacles. The proposed method is based on applying a genetic algorithm to find optimised trajectories in changing static and dynamic environments. The genetic algorithm considers genetic operators that are employed for path planning, along with high mutation criteria, the population of convergence, repopulation criteria and the incorporation of the destination point within the population. The effectiveness of this approach is validated through results obtained from both simulations and experiments, demonstrating that the genetic algorithm ensures efficient path planning and the ability to effectively avoid static and dynamic obstacles. A genetic algorithm for path planning of UAVs is proposed, achieving optimised paths in both static and dynamic environments for real-time tasks. In addition, this path planning algorithm has the properties to avoid static and moving obstacles in real-time environments.

Methods for conducting analysis, planning, and preservation of the historical and cultural potential of urban riverside areas

The article examines the decisive role of rivers in the historical, cultural, and civilizational development of the territories and peoples that inhabit them and explores possible ways of evaluating the historical and cultural potential of riverbanks for their integration into active urban planning. For this purpose, the principles and methodology of the architectural and landscape organisation of urban riverside areas have been outlined. One aspect of this methodology involves revealing the historical and cultural potential of riverside territories. Based on an analysis of UNESCO Heritage Sites regarding the connection of heritage objects with natural bodies of water, such as rivers, a specialised method has been proposed – for addressing these challenges – a method for identifying water bodies of historical and cultural heritage (using the Dnipro River in Kyiv, Ukraine, as a case study). It is noted that, for active urban planning and adaptation to climate change, riverside areas should be considered both as a unified territorial entity and as an independent object of urban planning design. This includes leveraging the unique historical and cultural potential of each city’s riverside territories and implementing planning solutions to sustain the natural and ecological state of river valleys, such as through the organisation of "blue-green" urban infrastructure.

Designing Resilient Coastal Cities: A Case Study of Climate-Compatible Urban Development in Keta, Ghana

Purpose: Coastal cities worldwide are increasingly vulnerable to the impacts of climate change, particularly sea-level rise and extreme weather events. Keta, a historic city in southeastern Ghana, is facing severe challenges from coastal erosion, flooding, and rising tides. This article explores resilient urban planning and architectural solutions designed to mitigate these risks. Methodology: By utilizing Keta as a case study, it investigates innovative policies, architectural designs, and sustainable infrastructure that can enhance climate resilience. Findings: The study stresses the necessity for a shift from reactive measures to proactive, long-term solutions that integrate resilience into urban development. Unique Contribution to Theory, Policy and Practice: Recommendations are provided for strengthening policy frameworks, adopting sustainable land-use practices, and promoting renewable energy integration to ensure the long-term sustainability of vulnerable coastal cities like Keta. Ultimately, this research makes available understandings into policy reform that supports national economic stability, promotes climate-compatible urbanization, and offers a model for resilience that may be adopted internationally to address similar climate challenges in coastal regions.

A 3D Model-Based Framework for Real-Time Emergency Evacuation Using GIS and IoT Devices

Advancements in 3D modelling technology have facilitated more immersive and efficient solutions in spatial planning and user-centred design. In healthcare systems, 3D modelling is beneficial in various applications, such as emergency evacuation, pathfinding, and localization. These models support the fast and efficient planning of evacuation routes, ensuring the safety of patients, staff, and visitors, and guiding them in cases of emergency. To improve urban modelling and planning, 3D representation and analysis are used. Considering the advantages of 3D modelling, this study proposes a framework for 3D indoor navigation and employs a multiphase methodology to enhance spatial planning and user experience. Our approach combines state-of-the art GIS technology with a 3D hybrid model. The proposed framework incorporates federated learning (FL) along with edge computing and Internet of Things (IoT) devices to achieve accurate floor-level localization and navigation. In the first phase of the methodology, Quantum Geographic Information System (QGIS) software was used to create a 3D model of the building’s architectural details, which are required for efficient indoor navigation during emergency evacuations in healthcare systems. In the second phase, the 3D model and an FL-based recurrent neural network (RNN) technique were utilized to achieve real-time indoor positioning. This method resulted in highly precise outcomes, attaining an accuracy rate over 99% at distances of no less than 10 metres. Continuous monitoring and effective pathfinding ensure that users can navigate safely and effectively during emergencies. IoT devices were connected with the building’s navigation software in Phase 3. As per the performed analysis, it was observed that the proposed framework provided 98.7% routing accuracy between different locations during emergency situations. By improving safety, building accessibility, and energy efficiency, this research addresses the health and environmental impacts of modern technologies.

Зеленые насаждения общественных пространств населенных пунктов Пермского края

Green spaces play a very important role in the structure of public landscaping facilities (parks, gardens, squares, boulevards), as they occupy more than 60% of the total area of the facilities and form the basis of the spatial structure of the territory. Sanitary and hygienic conditions, decorative planning solutions and the comfort of human stay in green spaces depend on the sanitary condition, aesthetic appearance, resistance to natural, climatic and environmental conditions of green spaces and on the spatial structure of the landscaping objects themselves. The most important issue for the Perm Region is the restoration and reconstruction of public spaces, including public landscaping facilities in various localities. Currently, as part of the implementation of the federal project "Comfortable Urban Environment", public landscaping facilities are being restored not only in large cities, but in small towns and other settlements of the Perm Territory. But in most cases, these public spaces are degraded to one degree or another, including in terms of landscaping. Currently, a significant part of the plantings in landscaped public areas requires the implementation of various forms of restoration to improve the aesthetic appearance and environmental conditions of the space itself. Taking timely measures will increase the longevity of the plantings and the attractiveness of the facility. This paper provides an analysis of the state of green spaces in public spaces using the example of a large city – Perm, a small one – Krasnovishersk and a settlement - Yugo-Kamsky settlement of the Perm Territory. In the course of the research, the species composition and number of trees and shrubs, the density of plantings, the sanitary condition and types of damage often encountered, the spatial structures of landscaping objects were determined and recommendations were given to improve the condition of green spaces. Keywords: SQUARE, PARK, SPECIES COMPOSITION, SANITARY CONDITION, TYPES OF DAMAGE, SPATIAL STRUCTURE, DENSITY OF PLANTINGS

Security and Compliance in Cloud ERP Systems: A Deep Dive into Workday's Framework

This paper provides a comprehensive analysis of the security and compliance framework within cloud- based ERP systems, with a particular focus on Workday, a leader in the market for enterprise resource planning (ERP) solutions. As businesses increasingly transition to cloud ERP systems, ensuring robust security and regulatory compliance has become critical to safeguarding sensitive data, maintaining operational integrity, and meeting industry-specific regulations. The paper begins by introducing the essential concepts of cloud ERP security, highlighting the challenges of data breaches, data integrity, and access control. It further explores Workday's advanced security infrastructure, including its encryption protocols, secure data storage, and real-time monitoring systems, as well as its adherence to global compliance standards such as GDPR, SOC 2, and ISO 27001. The analysis also emphasizes Workday’s tailored security features for specific industries like finance, healthcare, and government, demonstrating how its platform fosters customer trust and drives adoption across diverse sectors. Looking to the future, the paper discusses emerging trends, including the integration of Artificial Intelligence (AI), Machine Learning (ML), and blockchain technology, which hold potential for enhancing data security and compliance in cloud ERP environments. This deep dive into Workday’s security and compliance framework underscores its role in mitigating risks, ensuring regulatory adherence, and positioning itself as a trusted solution in an evolving cloud landscape. Keywords: AI/ML, Cloud ERP Security, Workday Security Framework, Cloud ERP Compliance, Workday Compliance Standards, Data Security, Workday Data Encryption, Regulatory Compliance, SOC 2 Compliance, Identity and Access Management, GDPR Compliance, Risk Mitigation.

From Classroom to Community: Service-Learning and the Sustainable Development Goals

Education for Sustainable Development (ESD) is crucial for equipping individuals with the competences needed to address the pressing social, economic, and environmental challenges of our time. Despite the recognized potential of service-learning in cultivating competences that can promote sustainable development, there is a lack of empirical research exploring the development of these competences among students. Hence, this study examined the effectiveness of service-learning as a pedagogical approach to ESD in fostering essential competences among students. The research involved 43 groups of students, who engaged in addressing various sustainable development issues through service-learning. A thematic analysis of students' written reflections revealed the development of six key competences: systems thinking, anticipatory, normative, strategic, interpersonal, and intrapersonal competences. These competences were nurtured through real-world engagement that enabled students to understand complex, interconnected sustainable development issues, anticipate future challenges, set ethical and practical goals, plan and implement strategic solutions, collaborate effectively, and display resilience amid challenges. The findings show the transformative potential of service-learning in aligning education with the Sustainable Development Goals (SDGs) and preparing students to contribute meaningfully to sustainable development by addressing community issues, creating impactful initiatives, and promoting personal and social transformation.

Adaptive Emergency Evacuation Routing: A Graph-Based Approach

Emergency evacuation plays a vital role in disaster management operations. The existing solutions for planning and routing emergency evacuations rely on preplanning based on prior information and lack adaptability to unprecedented conditions. This study introduces a novel adaptive method for emergency evacuation routing that dynamically reshapes the road network by actively determining and adjusting the direction of road segments and assigning traffic flow to them in order to improve the maximum possible flow of traffic evacuated from a set of dangerous zones to a set of safe zones. The proposed adaptive method revolves around a novel dynamic graph-based algorithm that iteratively and recursively distributes the traffic flow across the road network using a Depth First Search (DFS) approach. When the algorithm assigns the traffic flow to the road segments, it also determines the direction of the road segments to dynamically improve the performance of the evacuation process. The proposed method was implemented in a real-world evacuation scenario in the road network of Hoboken, New Jersey. The outcomes indicated a significant improvement of more than 74% in the number of successfully evacuated vehicles when the proposed algorithm was used, compared to state-of-the-art methods for evacuation routing that are unable to adjust road directions. The outcomes of this study help decision-makers and first responders develop dynamic and adaptive emergency evacuation plans for successful disaster management operations.

An explicit State-of-Charge planning solution for plug-in hybrid electric vehicle based on low-granularity prior-knowledge

The intervention of batteries in hybrid electric vehicles, when paired with an effective Energy Management Strategy (EMS), substantially improves fuel efficiency and reduces emissions in comparison to conventional internal combustion engine vehicles. The evolution of Intelligent Transportation Systems (ITS) has facilitated the possibility of predictive energy management (PEM) predicated on State-of-Charge (SoC) planning. Nevertheless, prevalent methodologies frequently encounter challenges in balancing optimization with real-time applicability. To address these limitations, we have devised an explicit SoC planning method that necessitates sparse traffic prior-knowledge, drawing inspiration from the optimal charge depletion behavior. This innovative method strategically determines the average SoC depletion rate for each anticipated driving road segment by integrating theoretical predictions of optimal depletion rate with experienced constraints. Capitalizing on prior knowledge of sparse traffic velocities and road grades, we have developed a hierarchical PEM framework that seamlessly integrates SoC planning – power split. The results of the simulation experiments reveal that the SoC trajectories and fuel consumption generated by this method are in close approximation to theoretically optimal benchmarks. Furthermore, the computational time of this method is in accordance with the demanding real-time requisites of onboard units even if hundreds of miles. Notably, this approach exhibits an enhanced robustness to predictive discrepancies, ensuring reliability and efficacy in dynamic driving cycles.

Research on Particle Swarm Optimization-Based UAV Path Planning Technology in Urban Airspace

Urban airspace, characterized by densely packed high-rise buildings, presents complex and dynamically changing environmental conditions. It brings potential risks to UAV flights, such as the risk of collision and accidental entry into no-fly zones. Currently, mainstream path planning algorithms, including the PSO algorithm, have issues such as a tendency to converge to local optimal solutions and poor stability. In this study, an improved particle swarm optimization algorithm (LGPSO) is proposed to address these problems. This algorithm redefines path planning as an optimization problem, constructing a cost function that incorporates safety requirements and operational constraints for UAVs. Stochastic inertia weights are added to balance the global and local search capabilities. In addition, asymmetric learning factors are introduced to direct the particles more precisely towards the optimal position. An enhanced Lévy flight strategy is used to improve the exploration ability, and a greedy algorithm evaluation strategy is designed to evaluate the path more quickly. The configuration space is efficiently searched using the corresponding particle positions and UAV parameters. The experiments, which involved mapping complex urban environments with 3D modeling tools, were carried out by simulations in MATLAB R2023b to assess their algorithmic performance. The results show that the LGPSO algorithm improves by 23% over the classical PSO algorithm and 18% over the GAPSO algorithm in the optimal path distance under guaranteed security. The LGPSO algorithm shows significant improvements in stability and route planning, providing an effective solution for UAV path planning in complex environments.

Державне регулювання безпекових технологій освітніх захищених просторів в зонах активних бойових дій: українські реалії та світовий досвід

The purpose of this work is the study of international experience and the substantiation of compliance with basic hygienic indicators when implementing atypical planning and construction solutions in new and existing institutions of general secondary education for the physical protection of participants in the educational process during the war in Ukraine. Materials and methods. Sanitary and hygienic, bibliometric and analytical methods were used in the work. Review. In Ukraine, in connection with the ongoing full-scale war and in order to protect students, there was an urgent need to solve the issue of protecting students, teachers and employees of the general institution of secondary education during the educational process, especially in those located in territories close to territories with active hostilities. The first special underground institution of general secondary education was opened in the city of Kharkiv – a bunker-type school, which corresponds to the current comprehensive policy of the Ministry of Education and Culture "School Offline". This institution of general secondary education is located in an underground space at a depth of 6 m. It is designed for a simultaneous capacity of 600 students of grades 1-11 (or 900 students in two shifts). The high cost of designing and building an underground institution of general secondary education limited its capacity, provision of a full set of functional groups of premises, including recreational, physical culture and sports, educational and production zones, provision of premises with natural lighting and insolation. For the implementation of this project, the architectural and planning and sanitary and hygienic standards have not been partially met, which may negatively affect the health of children and affect their quality of life in the future. In conditionally safe territories, it was proposed to arrange protected spaces in institutions of general secondary education, which also has a number of disadvantages and requires in-depth study. Conclusions. According to the results of the study of the international experience of extensive construction of underground institutions of general secondary education, none were found. However, the experience of building underground institutions of general secondary education with students staying during the school day is isolated, was carried out as an experiment and did not spread. The introduction of the latest constructive solutions (protected spaces) and the possibility of further expansion of the design and construction of underground institutions of general secondary education in Ukraine require careful study. Keywords. State regulation, world experience, institutions of general secondary education, bunker school, construction in underground space, educational protected spaces, children's safety.

The technology of restoration of the red brick facade on the example of an object of cultural heritage of regional significance “Mansion of the Philistine Galaktionov G.I.”

The article provides brief historical and archival information about the object of cultural heritage of regional significance “Mansion of the philistine Galaktionov G.I.”. A description of the decorative solution of the facades of the building, information about its spatial planning solution is given. The emphasis is placed on an unusual design solution of the main facade of the building – the vertical log cabin is lined with brickwork. Some results of complex engineering surveys are presented, from which it can be seen that the preserved structures of the building are in disrepair, there is a large percentage of masonry losses along the facades. However, it is still possible to preserve the original facing layer of the masonry of the main facade and technological solutions for its restoration are given. The description of the measures after the work on the preservation of the red brick facade is given. An assertion is made about the individuality of the developed technology, since each object of cultural heritage is unique from the point of view of the degree of preservation of structures.