{"id":53520,"date":"2025-08-12T12:10:37","date_gmt":"2025-08-12T04:10:37","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/53520.html"},"modified":"2025-08-12T12:10:37","modified_gmt":"2025-08-12T04:10:37","slug":"2025%e4%b8%96%e7%95%8c%e6%9c%ba%e5%99%a8%e4%ba%ba%e5%a4%a7%e4%bc%9a%ef%bd%9c%e5%85%b7%e8%ba%ab%e6%99%ba%e8%83%bd%e6%9c%ba%e5%99%a8%e4%ba%ba%e5%8d%81%e5%a4%a7%e5%8f%91%e5%b1%95%e8%b6%8b%e5%8a%bf","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/53520.html","title":{"rendered":"2025\u4e16\u754c\u673a\u5668\u4eba\u5927\u4f1a\uff5c\u5177\u8eab\u667a\u80fd\u673a\u5668\u4eba\u5341\u5927\u53d1\u5c55\u8d8b\u52bf"},"content":{"rendered":"

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\u8d8b\u52bf\u4e5d<\/p>\n

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\u00a0<\/p>\n

10 Trends of<\/p>\n

Embodied Intelligent Robots<\/p>\n

\u00a0<\/p>\n

TREND<\/p>\n

1<\/p>\n

Embodied Cognition Driven by the Synergy of Physical Practice, Physical Simulators, and World Models<\/p>\n

\u00a0<\/p>\n

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Physical practice\u00a0is the essence of embodied intelligence.\u00a0Physical simulators\u00a0construct high-fidelity training environments, while\u00a0world models\u00a0provide the internal characteristics of the environment. The integration of these three elements enables the creation of rich,\u00a0effective and realistic environments\u00a0for training embodied intelligent robots in perceptual and cognitive abilities regarding both contact and non-contact interactions with the environment, laying a solid foundation for decision-making and control.<\/p>\n

\u00a0<\/p>\n

TREND<\/p>\n

2<\/p>\n

Empowering Embodied Decision-Making via Multimodal Large Model<\/p>\n

\u00a0<\/p>\n

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Multi-level end-to-end embodied decision-making:\u00a0Inspired by multimodal large models, \u00a0the research on cognition and planning with mathematical and physical foundations, integrated with life sciences and combined with real-time control modules, significantly enhances the task generalization ability of embodied intelligent robots in unstructured environments.<\/p>\n

\u00a0<\/p>\n

TREND<\/p>\n

3<\/p>\n

Embodied Intelligent Control via Integrating Model Prediction, Reinforcement Learning and Life Sciences<\/p>\n

\u00a0<\/p>\n

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By integrating the dynamic optimization capabilities of\u00a0model predictive control, adaptive strategies of\u00a0reinforcement learning, and the\u00a0redundant multi-loop control mechanisms from life sciences, an\u00a0embodied intelligent robot control system\u00a0is constructed to improve the generalization and adaptability of embodied intelligent robot control in dynamic environments.<\/p>\n

\u00a0<\/p>\n

TREND<\/p>\n

4<\/p>\n

Generative AI for Embodied Intelligent Robot Design<\/p>\n

\u00a0<\/p>\n

<\/p>\n

Generative AI-driven intelligent robot design realizes unified optimization of motors, reducers, drivers, structures, connectors, and materials. In combination with research and development technologies of robotic structure, it\u00a0achieves co-optimization of hardware and control strategies\u00a0in physical \u00a0simulators, enabling automatic exploration of task-optimal embodied intelligent robot designs.<\/p>\n

\u00a0<\/p>\n

TREND<\/p>\n

5<\/p>\n

Highly Synergistic and Dynamically Adaptive Software\/Hardware Consistency for Embodied Intelligence<\/p>\n

\u00a0<\/p>\n

<\/p>\n

Embodied intelligent robots require\u00a0consistent software\/hardware co-design. By predefining\u00a0interface specifications\u00a0of algorithms during hardware development and embedding\u00a0physical constraints\u00a0of hardware into algorithm design, system-level consistency and optimization are achieved through joint simulation and validation.<\/p>\n

\u00a0<\/p>\n

TREND<\/p>\n

6<\/p>\n

\u201cManufactory\u201d of Embodied Intelligent Robots<\/p>\n

\u00a0<\/p>\n

<\/p>\n

In the\u00a0simulation environment, research and development efforts such as natural language interaction, environment generation, robot body design, decision-control algorithms, and software-hardware consistency algorithms are integrated into an organic whole, enabling \u00a0rapid design and manufacturing\u00a0of high-quality embodied intelligent robot systems according to specific performance and requirements.<\/p>\n

\u00a0<\/p>\n

TREND<\/p>\n

7<\/p>\n

Large-Scale and High-Quality Dataset for Embodied Intelligence<\/p>\n

\u00a0<\/p>\n

<\/p>\n

The construction of\u00a0large-scale and high-quality datasets for embodied intelligence\u00a0through physical entity collection and simulation synthesis can enhance embodied intelligent robots\u2019 capabilities in morphological optimization, multimodal training efficiency, and cross-scenario policy transfer.<\/p>\n

\u00a0<\/p>\n

TREND<\/p>\n

8<\/p>\n

Advances in Embodied Intelligent Robot Swarms and the Collaboration with Humans<\/p>\n

\u00a0<\/p>\n

<\/p>\n

Integrating\u00a0multi-agent coordination mechanisms\u00a0to construct embodied intelligent robot swarms, while continuously improving the safety of embodied intelligent agents and their ability to empathize with humans, will facilitate such robots\u2019 entry into human society and realize their integration with humans.<\/p>\n

\u00a0<\/p>\n

TREND<\/p>\n

9<\/p>\n

Interdisciplinary Open Community for Embodied Intelligent Robots<\/p>\n

\u00a0<\/p>\n

<\/p>\n

The development of embodied intelligent robots requires\u00a0collaboration across multiple disciplines, such as information sciences, engineering and materials sciences, mathematical and physical sciences, and life sciences. This initiative will bring together experts \u00a0and scholars worldwide to promote technical discussions in the field of embodied intelligence, and facilitate in-depth integration and collaborative development throughout the industrial chain.<\/p>\n

\u00a0<\/p>\n

TREND<\/p>\n

10<\/p>\n

Safety Assessment and Ethical Development for Embodied Intelligent Robots<\/p>\n

\u00a0<\/p>\n

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\u00a0<\/p>\n

<\/p>\n

Through\u00a0behavior norm verification,\u00a0decision interpretability analysis, and\u00a0data security research, a safety assessment framework and ethical norms for embodied intelligent robots will be established to ensure decision reliability and behavioral safety in complex and open environments.<\/p>\n

\u6587\u7ae0\u6765\u6e90：\u4e2d\u56fd\u7535\u5b50\u5b66\u4f1a<\/p>\n

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\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"

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