物理AI：机器人首当其冲，Arm发布未来机器人技术核心方向_老虎社区_美港股上老虎

物理AI：机器人首当其冲，Arm发布未来机器人技术核心方向

电子发烧友01-12

IDC发布预测数据显示，到 2029 年全球机器人市场规模将超过 4,000 亿美元。其中，中国市场占据近半份额，并以近 15% 的复合增长率位居全球前列，成为推动全球产业增长的重要引擎。此外，摩根士丹利在《机器人年鉴》中预测，基准情形下，全球机器人硬件销售额将从 2025 年的约 1,000 亿美元激增至 2030 年的 5,000 亿美元，2040 年达到 9 万亿美元，并在 2050 年攀升...

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technology","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"SNVD.UK":0.6,"NVDU":0.6,"NVDX":0.6,"NVIW.SI":0.6,"NVDS":0.6,"NVD2.UK":0.6,"ARM":1.93,"2NVD.UK":0.6,"NVDY":0.6,"NVDS.UK":0.6,"NVD":0.6,"NVD3.UK":0.6,"3NVD.UK":0.6,"NVDD":0.6,"NVDA":0.9},"content_text":"IDC发布预测数据显示，到 2029 年全球机器人市场规模将超过 4,000 亿美元。其中，中国市场占据近半份额，并以近 15% 的复合增长率位居全球前列，成为推动全球产业增长的重要引擎。此外，摩根士丹利在《机器人年鉴》中预测，基准情形下，全球机器人硬件销售额将从 2025 年的约 1,000 亿美元激增至 2030 年的 5,000 亿美元，2040 年达到 9 万亿美元，并在 2050 年攀升至 25 万亿美元。这一预测仅涵盖硬件销售，若加上软件服务、维护及供应链相关收入，市场规模可能成倍增长。到 2050 年，中国将占据全球机器人销量的约 26%，其中在工业机器人和无人机领域的份额更高。作为机器人产业的核心支撑，半导体领域的市场增长同样势头强劲。根据 MarketsandMarkets 的预测，全球机器人用半导体市场规模将从2025年的112.3亿美元增至2030年的412.4亿美元，年复合增长率达29.7%‌‌。机器人技术核心方向一、世界模型重塑物理AI开发，降低机器人研发门槛世界模型将成为机器人等物理AI系统开发的关键基础工具，依托高保真模拟技术支撑的虚拟环境加速研发迭代。世界模型可构建精准反映真实物理规律的虚拟场景，为机器人提供沙盒化的“AI仿真测试平台”，支持开发者在系统部署前完成训练、压力测试与迭代优化，大幅降低研发风险并显著缩短开发周期。这一技术对制造业、物流、自动驾驶等领域的机器人应用至关重要，将成为企业的核心竞争刚需与推动物理 AI 技术突破的核心催化剂。例如，可用于仓储等复杂场景的机器人研发与性能验证。二、自主 AI 智能体崛起，推动机器人多场景协同AI将从辅助工具进化为自主智能体，多智能体编排技术将在机器人领域广泛应用。未来机器人将具备有限人工干预下的感知、推理与行动能力，多智能体协同模式将在工业制造、物流等场景全面普及。例如，工厂自动化中，“监督式 AI” 可自主监控生产流程、检测异常工况、预测产能瓶颈，并自主启动纠偏措施，联动工业机器人完成高效协同作业；物流场景中，智能体系统可持续监控物流流向，主动调度机器人完成补货、路径调整或向管理人员发出预警，替代传统被动响应模式。三、物理 AI 规模化落地，驱动机器人产业发展物理 AI 将实现规模化部署，新一代智能机器人将重塑医疗健康、制造、采矿、交通运输等多行业生产力格局。依托多模态模型与更高效训练、推理管线的技术突破，物理 AI 将赋能各类自主机器人，不仅能显著提升生产效率，还可在对人类存在安全风险的环境中稳定可靠运行。值得关注的是，面向汽车与机器人自动化场景的通用计算平台将逐步涌现，车载芯片有望通过技术复用与适配，应用于人形机器人、工业机器人领域，进一步提升规模经济效益，加速物理 AI 系统的研发与落地进程。Arm在机器人领域的优势随着物理AI 时代的加速演进，汽车正从交通工具转变为由人工智能(AI) 定义的平台，可支持自动驾驶、AI 驱动的信息娱乐功能及个性化车载体验。与此同时，机器人技术也迈入了新篇章——人形机器人、自主移动机器人(AMR) 和智能工业系统等都将具备实时感知、推理与决策响应的能力。要充分释放这类智能设备的潜力，需要一套“安全为先”的计算平台，既具备卓越的算力性能、灵活的可扩展性，又能实现极致能效。Arm 正处于这场变革的核心，其面向汽车领域打造的成熟解决方案，可通过技术复用与场景化适配，无缝迁移至人形机器人、工业机器人领域，叠加 Arm 技术的强大生态协同能力，为机器人产业的智能化发展注入核心动力。如今，Arm处理器已广泛应用于各类机器人产品，并持续与全球生态伙伴深度协作，凭借“高能效+高可靠+高适配”的技术优势，成为未来AI 机器人发展的核心技术基石。英伟达、云深处科技基于Arm架构，成功开发机器人计算平台以 Arm Neoverse 作为CPU核心基础，NVIDIA 推出了搭载 NVIDIA Jetson Thor 的前沿计算平台。该平台专为实时、多模态AI 工作流打造，可支持机器人同步实现感知、推理与行动，而Neoverse V3AE 赋予的卓越单核性能与每瓦效率，保障设备并行运行多AI 模型且不影响响应速度。Neoverse V3AE 单线程性能卓越、可扩展性强，可并行运行多个复杂AI 模型。依托Arm 领先的每瓦性能，系统在边缘机器人上可持续运行先进AI 工作负载，优势整合后可实现多传感器数据融合、生成式AI 运行，并在高响应要求场景下做出安全实时决策。NVIDIA Jetson Thor 在多领域展现出强大应用价值。在人形机器人领域，它助力设备实现自然交互，还支持机器人在动态非结构化环境中高效执行真实作业任务并实现人机无缝协作；在工业自动化场景中，它提升自主设备与机械臂的效率和安全性，同时赋能机器人完成工业码垛、拆垛及物料箱搬运等复杂作业，更支持人形机器人实现自主换电功能以保障持续作业；在医疗系统中，它支持医疗机器人执行监护、康复及手术辅助等任务；同时，平台搭载性能提升 3.1 倍的 CPU，整合更多核心与更强GPU性能，进一步夯实先进机器人实时控制的算力基础。云深处科技从 x86 架构转向 Arm 架构的瑞芯微RK3588 芯片，突破能效、散热等限制，为机器人动态运动提供高效算力支撑。Arm架构凭借精简软件栈、高能效、小巧强悍三大优势，高效赋能云深处科技机器人开发。精简的软件栈：凭借Arm架构，云深处科技能够以最少的依赖项采用基于Linux的精简系统，是运行定制开发的运动控制算法和强化学习模型的理想之选。高能效：与功耗约30瓦的传统英特尔平台相比，基于Arm架构的系统仅消耗10瓦出头的功耗。功耗和散热的大幅优化，使机器人续航更长、电池更小、散热更简单。小巧强悍：只需单个基于Arm架构的SoC，就能驱动所有12个电机，控制站立、行走和奔跑等运动模式。即便运行了基于强化学习的运动控制器，RK3588芯片仍留有充足的性能空间，可支持更多附加功能。","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"0","news_tag":"","news_rank":0,"symbols":[],"gpt_button":0,"need_auth":false,"code":"91000000","status":"200"},"commentList":[],"hasMoreComments":false,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":0,"favoriteSize":1,"likeStatus":false,"favoriteStatus":false},"isCrawlerRequest":true}