Autonomous driving paper index
Triboelectric Nanogenerators in Military: Recent Progress and Critical Challenges
One-line summary
The rapid evolution of modern warfare toward distributed, intelligent, and global stealth has posed severe energy supply and information perception bottlenecks for combat nodes.
Engineering notes
Key topics: autonomous driving, deployment, perception. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
The rapid evolution of modern warfare toward distributed, intelligent, and global stealth has posed severe energy supply and information perception bottlenecks for combat nodes. Traditional energy supply strategies are unable to meet the strategic needs of long-range stealth operations and extreme environmental survival. Triboelectric nanogenerators provide a disruptive path for constructing self-sustaining military microsystems with high-efficiency and zero-power-sensing characteristics. This review establishes a comprehensive framework that systematically evaluates recent technological advances across an escalating hierarchy, encompassing individual soldier combat platforms, unmanned combat systems, strategic aerospace equipment, and special tactical scenarios. Crucially, moving beyond generic laboratory demonstrations, this review adopts a rigorous defense engineering perspective by conducting an integrated failure mode analysis to evaluate device degradation under severe battlefield stressors. Furthermore, it critically analyzes the primary engineering bottlenecks currently hindering military adoption, such as inherent impedance mismatch and scalable manufacturing barriers, and proposes targeted mitigation strategies. To systematically validate these solutions, we explicitly propose a concise evaluation framework strictly aligned with established military testing protocols. Ultimately, this review outlines several forward-looking strategic priorities, thereby constructing a highly actionable roadmap to accelerate the practical deployment of self-driven intelligent technologies.
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