14日，历经十多天的中巴"勇士-9"反恐联合演习圆满结束，中方参演部队全部归建回国。 当地时间12日，演习结束仪式在巴基斯坦帕比国家反恐训练中心举行。随后中方参演部队启程回撤，采用航空投送和陆航、无人机空中转场方式，分多批次 于14日全部返回国内归建。 中方参演部队 杨坤：在此次回撤行动中，我们与巴基斯坦军地多方协调联络，密切组织运输投送和通关通检，确保任务部队回撤安全顺利、万无一失。 自12月初开训以来，中巴两军以联合打击恐怖主义为背景，以"联合反恐清剿打击行动"为课题，采取混编联训的模式，共同完成了山地清剿、人质营救、联 合火力打击等课目训练。 中方参演部队 刘哲良：通过十多天的联演，中巴双方围绕恐怖活动新形势、新特点，针对性组织联合训练演习，进一步拓展了军事反恐合作的深度和广 度，展现了中巴联合打击恐怖主义的决心和意志。 在演习最后阶段，中巴参演部队在巴基斯坦帕比国家反恐训练中心展开全流程全要素实兵实弹演习。双方共同组织陆空联合行动，并出动中高空长航时无人 机以及无人机蜂群、自杀式穿越机、排爆机器人等多型无人装备，对假想目标完成侦察监视、封锁控制、分区清剿、纵深追歼等作战任务。 中方参演部队 刘康：在实 ...

央视网消息：2025年智能机器人大赛决赛12月9日在北京昌平落下帷幕。大赛聚焦应急救援、康复养老、全域创新三大核心赛道，集中展现我 国智能机器人在技术自主化、场景多元化、服务人性化三大维度的突破性进展。 记者走进安全应急赛道的决赛场。在模拟排爆任务中，一台机器人突然发生侧翻，正当众人捏紧拳头时，它没有停滞"趴窝"，而是缓缓伸出机 械臂，如乌龟撑地般稳稳翻转身体，迅速恢复作业姿态。 参赛队伍工程师蔡艳波介绍，在真实排爆任务现场，危机四伏，排爆机器人在作业过程中一旦意外倾覆，让人工去回收无异于直面生死考验。 通过自身的姿态调整，来保证排爆任务的继续推进，最大限度地降低涉险人员的涉险概率。 除了自救，机器人也在成为守护人类的"智能哨兵"。在安全巡检应用中，它们凭借多维度感知系统主动排查风险隐患，通过各类传感器实时捕 捉环境数据并即时预警，成为人类延伸至危险环境的"远程感官"。 参赛队伍工程师秦倩倩介绍，巡检机器人高度集成了多传感器以及AI识别算法，在园区、厂区等多种实际场景的巡检过程中，可以同步完成 噪声检测、人员识别、火情预警等多种智能识别功能。同时，通过实时数据回传，以及机器端的声光报警，可以达到及时响应的目的 ...

Group 1 - The 2025 High-Quality Development Forum for Listed Companies and the 27th Golden Bull Award Ceremony took place in Nantong, Jiangsu, with the theme "Moving Towards the New, Achieving with Reality, and Intelligent Future" [1] - Liu Peng, the Director, Deputy General Manager, and Secretary of the Board of Jingpin Special Equipment, won the "Golden Bull Secretary Award" at this event [1] - The Golden Bull Award, established in 1999 by China Securities Journal, aims to create a credible platform for communication and brand display in the capital market, recognizing outstanding contributions in corporate governance, information disclosure, and investor relations management [1] Group 2 - Jingpin Special Equipment, founded in 2009, is a national high-tech enterprise specializing in the research, production, and sales of optoelectronic reconnaissance equipment and military robot systems [2] - The company's main products include various models of drone optoelectronic pods, handheld optoelectronic reconnaissance devices, individual night vision goggles, handheld wall-penetrating radars, bomb disposal robots, multipurpose robots, and portable reconnaissance robots [2] - As a national high-tech enterprise in the military industry, Jingpin has focused on the fields of military informationization, intelligence, and automation, successfully developing multiple products that have been deployed in frontline troops [2]

Core Insights - The article highlights the integration of unmanned systems into military training and operations, showcasing the advancements in technology that enhance combat effectiveness and safety [1][2][4]. Group 1: Tactical Exercises - A recent tactical exercise by the 77th Group Army involved various unmanned systems responding to simulated battlefield scenarios, demonstrating the effectiveness of integrating these technologies into combat training [1]. - The exercise included the use of drones, bomb disposal robots, unmanned transport vehicles, and underwater rescue systems, showcasing a comprehensive approach to modern warfare [1][3]. Group 2: Overcoming Challenges - The introduction of new equipment addresses critical challenges faced by soldiers, such as the dangers associated with bomb disposal and reconnaissance in hostile environments [2]. - Soldiers reported that the use of robots for bomb disposal significantly increases safety and efficiency, allowing them to focus on strategic operations rather than manual tasks [3]. Group 3: Training Innovations - The integration of unmanned systems has sparked a wave of innovation in training methods, with a focus on achieving effective collaboration between manned and unmanned units [4][6]. - The army has developed a new training model that emphasizes realistic simulations and cross-training among different units to enhance operational readiness [4][6]. Group 4: Resource Integration - The article emphasizes the importance of resource integration and collaboration among different units to achieve superior battlefield performance [6]. - The training approach includes theoretical learning, practical exercises, and real-time data sharing to ensure all units can operate cohesively in complex scenarios [6].