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Since its establishment, Future Science and Technology Research has always adhered to the editorial philosophy of "insight into technological trends, empowerment of innovative breakthroughs, and connection of global wisdom". It strictly adheres to the bottom line of academic integrity, upholds international standard layout norms, and implements a strict selection mechanism of "three reviews and three proofreadings". Relying on its forward-looking research perspective, profound academic accumulation, and distinct technological characteristics, It is highly favored by research teams from universities around the world, key R&D personnel from technology enterprises, experts and scholars from research institutes, and policymakers. This journal is an Open Access journal. All published articles are freely available for download to readers worldwide. At the same time, it is included in many well-known domestic and international retrieval platforms such as China Core Database of Science and Technology and China National Knowledge Infrastructure (CNKI), ensuring the efficient dissemination and wide academic influence of cutting-edge scientific and technological achievements.
As an international open-source professional journal focusing on the innovative development of future science and technology fields, this journal aims to break the boundaries of traditional disciplines and technical barriers, and build a cross-field and cross-industry platform for scientific and technological exchanges Comprehensively reflect the new theories, technologies, methods and applications in cutting-edge scientific and technological fields such as artificial intelligence, information technology, biotechnology, new materials, new energy, aerospace, intelligent manufacturing and digital economy. Whether it is the original innovation in basic science, the breakthrough and research of core technologies, the exploration of interdisciplinary integration, or the transformation and application of scientific and technological achievements and the practice of industrial empowerment, all are the core focus directions of this journal. We are committed to collecting research achievements that are original, forward-looking and of industrial value, promoting academic dialogue and technical collaboration among researchers from different fields and regions around the world, and providing solid academic support for promoting self-reliance and self-strengthening in science and technology and contributing to the sustainable development of human society.
Journal scope It covers artificial intelligence and robotics (machine learning, deep learning, intelligent systems, etc.), information technology and digital technology (big data, cloud computing, blockchain, quantum computing, etc.), biotechnology and life sciences (gene editing, synthetic biology, biopharmaceuticals, etc.), new materials and advanced manufacturing (special materials, 3D Printing, intelligent sensing, etc., new energy and low-carbon technologies (renewable energy, energy storage technology, carbon reduction technology, etc.), aerospace and space technologies (deep space exploration, satellite technology, aerospace equipment, etc.), digital economy and science and technology management (science and technology policies, innovation ecosystems, industrial digitalization, etc.) and cross-integration fields (such as human-computer interaction, brain-computer interfaces, bioinformatics, green science, etc.) The academic achievements in various fields such as basic research, applied research, technology reviews, case analyses, and patent interpretations, which take into account both theoretical innovation and practical implementation, comprehensively serve the academic development, technological progress, and industrial upgrading in the future field of science and technology.
This journal is a peer-reviewed professional academic publication. It adheres to an international high-standard and strict review process, and has formed an editorial board and review team composed of the world's top experts to ensure the academic standardization, scientific rigor and technical foresight of the published results. The editor warmly welcomes scholars from all over the world to submit their research on the cutting-edge hotspots, core challenges, technical bottlenecks and industrial pain points in the field of future science and technology. In particular, original research with an interdisciplinary integration perspective, disruptive innovation value and significant application prospects is encouraged to jointly contribute to the construction of an open, inclusive, collaborative and sustainable global scientific and technological academic ecosystem.
Qingdao University of Technology, Shandong Qingdao, 266520;
Abstract：Aiming at the core problems in urban low-altitude logistics scenarios, such as complex airspace environment, diverse constraint conditions, and insufficient path planning adaptability, this paper proposes a multi-constraint path planning scheme integrating an adaptive improved particle swarm optimization (PSO) algorithm and digital twin simulation technology to realize the coordinated optimization of UAV delivery efficiency, flight safety, and operational costs. Firstly, it systematically sorts out the core constraint factors of urban low-altitude logistics, constructs a four-dimensional constraint system covering airspace compliance, equipment performance, task requirements, and operational costs, and clarifies the boundary conditions and quantitative standards of each constraint. Secondly, to address the defects of traditional optimization algorithms, such as low convergence accuracy and proneness to falling into local optimal solutions, the traditional PSO algorithm is improved by introducing a dynamic weight adjustment mechanism and an obstacle avoidance adaptive factor, and a multi-objective fitness function is constructed to balance path optimality and scenario adaptability. Finally, a 3D simulation platform for urban low-altitude logistics is built based on digital twin technology, integrating multi-source data such as real urban terrain, building distribution, and airspace control zones, and comparative experiments are carried out in a typical urban delivery area. The research results show that compared with the traditional PSO algorithm and A* algorithm, the proposed algorithm has significant improvements in path planning efficiency, energy consumption control, and obstacle avoidance stability, which can effectively adapt to the complex multi-constraint scenarios of urban low-altitude logistics and provide theoretical support and engineering practice reference for the intelligent planning of UAV logistics routes.
Keywords：Low-Altitude Logistics; Unmanned Aerial Vehicle (UAV); Path Optimization; Multi-Constraint System; Improved Particle Swarm Optimization Algorithm; Digital Twin; Simulation Analysis
References
[1] Guan J ,Ye S ,Yi W .MSCPSO: A multi-strategy cooperative particle swarm optimization algorithm for UAV path planning[J].Expert Systems With Applications,2026,
[2] Zhang M ,Luo M ,Kang H .Multi-Strategy Improved Pelican Optimization Algorithm for Engineering Optimization Problems and 3D UAV Path Planning[J].Biomimetics,2026,11(1):73-73.
