文｜张子怡 算法研发要求同步升级。因此，上海交通大学交龙战队的步兵机器人搭载边缘计算模块，通过神经网络 实现敌方装甲板、能量机关扇叶识别，同步完成运动预测与弹道解算，支持远距离精准打击动态目标。 相关技术既提升实战性能，更推动深度学习等前沿视觉算法在复杂动态环境中的应用探索。 东北大学TDT战队的工程机器人采用关节式串联机械臂与逆运动学解算技术，结合自定义控制器这种符 合直觉的人机交互形式，高效完成三维特殊角度的矿石兑换，在比赛中持续积累经济优势，为高强度对 抗提供支撑。 中国科学技术大学RoboWalker战队基于激光雷达与先进算法，实现规划导航、避障及多机通讯，进行 自主追击、进攻、基地保护等智能决策，在赛场复杂环境下灵活应对"攻防"需求。相关技术能够引导学 生关注前沿AI决策算法，对接自动化工业生产、辅助驾驶、安防巡检等智能产业需求。 机甲大师赛初期引入空中机器人，以轻量化、高负载为目标，持续提升载重率要求，推动参赛队在轻量 化与动力载荷平衡上创新。25赛季中，中国石油大学（华东）RPS战队的空中机器人表现突出，整机重 量仅为12.4kg，可负载5kg官方物资，在7分钟的比赛时间中进行高效输出，紧贴应急 ...

Core Insights - The RoboMaster 2025 National Competition concluded with Shanghai Jiao Tong University's team winning the championship, while teams from the University of Science and Technology of China, South China University of Technology, and Northeast University secured the second, third, and fourth places respectively [1][3]. Group 1: Technological Advancements - The competition showcased significant advancements in robot technology, particularly in the development of bipedal robots capable of navigating complex terrains, including stair climbing and self-resetting after falls [3]. - Teams focused on optimizing structures and algorithms to enhance robot load capacity, mobility, and adaptability to various terrains, which aligns with practical applications in security inspections and disaster rescue [3][5]. Group 2: Application of AI and Algorithms - The champion team's robot utilized edge computing and neural networks for enemy armor recognition and motion prediction, enhancing its combat capabilities and exploring applications of deep learning in dynamic environments [5]. - The runner-up team implemented laser radar and advanced algorithms for autonomous navigation, obstacle avoidance, and multi-machine communication, addressing complex offensive and defensive strategies [5]. Group 3: Educational Impact - The competition provided participants with a comprehensive engineering experience, requiring them to engage in demand analysis, design, prototyping, and iterative optimization, simulating real-world challenges in research and industry development [5][7]. - This "full-process practical" model prepares students for future careers in intelligent security, disaster rescue, and low-altitude economy sectors, establishing a solid foundation for practical application [7].