【ZiDongHua 之“自動(dòng)化學(xué)院派”收錄關(guān)鍵詞：世界機(jī)器人大會(huì) 具身智能機(jī)器人  世界機(jī)器人合作組織 中科院自動(dòng)化所】

大會(huì)發(fā)布 | 具身智能機(jī)器人十大發(fā)展趨勢(shì)?

編者按

/ WRC2025

2025世界機(jī)器人大會(huì)于8月8日開(kāi)幕，開(kāi)幕式上發(fā)布了《2025具身智能機(jī)器人十大發(fā)展趨勢(shì)》，以下為全文。

趨勢(shì)一

第一，物理實(shí)踐、物理模擬器與世界模型協(xié)同驅(qū)動(dòng)的具身感認(rèn)知。物理實(shí)踐是具身智能的本質(zhì)，物理模擬器可以構(gòu)建高保真的訓(xùn)練環(huán)境，世界模型可以提供環(huán)境當(dāng)中比較本質(zhì)的內(nèi)部特征。三者融合既可以保證豐富、有效、真實(shí)的環(huán)境，也可以用于訓(xùn)練具身智能機(jī)器人與環(huán)境的接觸和非接觸交互的感認(rèn)知能力，為其決策和控制奠定基礎(chǔ)。

趨勢(shì)二

第二，多層次端到端的具身決策。由多模態(tài)大模型啟發(fā)的，具有數(shù)理基礎(chǔ)的認(rèn)知與規(guī)劃研究，與生命科學(xué)家的成果融合，并與實(shí)時(shí)的控制模塊融合，可以顯著增強(qiáng)具身智能機(jī)器人在非結(jié)構(gòu)化環(huán)境下的泛化性和實(shí)用性。

趨勢(shì)三

第三，從控制角度來(lái)看，可以融合模型預(yù)測(cè)、強(qiáng)化學(xué)習(xí)和生命科學(xué)的具身智能控制。一方面可以把模型預(yù)測(cè)控制的動(dòng)態(tài)優(yōu)化能力，把強(qiáng)化學(xué)習(xí)自適應(yīng)決策融合起來(lái)，更進(jìn)一步的與生命科學(xué)的冗余多環(huán)路控制機(jī)制相融合。這樣的話，可以更加讓具身智能機(jī)器人向人發(fā)展，實(shí)現(xiàn)具身智能的新控制，提升其在新環(huán)境當(dāng)中的適應(yīng)性和高性能。

趨勢(shì)四

第四，生成式人工智能驅(qū)動(dòng)的具身智能機(jī)器人設(shè)計(jì)。通過(guò)對(duì)于電機(jī)、減速器、驅(qū)動(dòng)器、結(jié)構(gòu)、連接件和材料的統(tǒng)一優(yōu)化，同時(shí)與工材領(lǐng)域的科學(xué)成果相結(jié)合，在物理模擬器當(dāng)中實(shí)現(xiàn)硬件與控制策略的協(xié)同優(yōu)化，可自動(dòng)探索任務(wù)中實(shí)現(xiàn)最優(yōu)的具身智能的機(jī)器人設(shè)計(jì)。

趨勢(shì)五

第五，高度協(xié)同與動(dòng)態(tài)適配的具身智能軟硬件一致性。具身智能機(jī)器人需要軟硬件的一致性，在硬件開(kāi)發(fā)的階段需預(yù)置適配算法的接口規(guī)范，在算法的設(shè)計(jì)當(dāng)中又會(huì)內(nèi)嵌物理約束，就是軟中有硬，硬中有軟，并且通過(guò)聯(lián)合仿真驗(yàn)證，就是有軟有硬的情況下，讓系統(tǒng)更加保持一致，讓軟件模塊更加接近硬件，讓整體系統(tǒng)更加符合我們的軟硬件一致性的期望。

趨勢(shì)六

第六，具身智能機(jī)器人大工廠，在仿真環(huán)境當(dāng)中實(shí)現(xiàn)自然語(yǔ)言交互、環(huán)境生成、機(jī)器人本體設(shè)計(jì)、決策-控制算法以及軟硬件一致性算法等研發(fā)，讓他們有機(jī)的結(jié)合在一起，并且反復(fù)進(jìn)化。這樣的系統(tǒng)可以根據(jù)性能和需求實(shí)現(xiàn)快速設(shè)計(jì)和實(shí)現(xiàn)高質(zhì)量具身智能機(jī)器人系統(tǒng)，為社會(huì)服務(wù)。

趨勢(shì)七

第七，具身智能大規(guī)模高質(zhì)量數(shù)據(jù)集，基于物理實(shí)體采集與仿真合成構(gòu)建大規(guī)模高質(zhì)量具身智能數(shù)據(jù)集。這里高質(zhì)量是一個(gè)關(guān)鍵，關(guān)于大規(guī)模，科研的期望是讓它規(guī)模要變小。同時(shí)可以顯著提升具身智能機(jī)器人的本體構(gòu)型優(yōu)化、多模態(tài)訓(xùn)練效率及跨場(chǎng)景策略遷移能力。

趨勢(shì)八

第八，具身智能機(jī)器人集群及與人協(xié)同的發(fā)展，融合多智能體的協(xié)同機(jī)制，構(gòu)建具身智能機(jī)器人集群。同時(shí)不斷提升具身智能機(jī)器人的安全性，及其與人的共情能力，讓具身智能機(jī)器人真正走向我們，真正走向人類(lèi)，成為人類(lèi)的朋友。

趨勢(shì)九

第九，跨學(xué)科的具身智能機(jī)器人開(kāi)源社區(qū)。首先具身智能機(jī)器人的發(fā)展需要信息科學(xué)、工程與材料科學(xué)、數(shù)學(xué)物理科學(xué)、生命科學(xué)等多學(xué)科協(xié)作，將在全球范圍內(nèi)聚集各領(lǐng)域的頂級(jí)科學(xué)家和工程人員，促進(jìn)具身智能領(lǐng)域的技術(shù)探討，助力產(chǎn)業(yè)鏈的上下游深度融合和協(xié)作發(fā)展。

趨勢(shì)十

第十，面向具身智能機(jī)器人的安全評(píng)估與倫理建設(shè)，通過(guò)行為規(guī)范驗(yàn)證、決策可解釋性分析，和數(shù)據(jù)安全性研究等，能夠確保建立面向具身智能機(jī)器人的安全評(píng)估體系和倫理規(guī)范。確保在復(fù)雜開(kāi)放環(huán)境中決策的可靠性、可解釋性以及行為的安全性，這才使得具身智能機(jī)器人能夠走向我們的服務(wù)行業(yè)。

10 Trends of

Embodied Intelligent Robots

TREND

1

Embodied Cognition Driven by the Synergy of Physical Practice, Physical Simulators, and World Models

Physical practice is the essence of embodied intelligence. Physical simulators construct high-fidelity training environments, while world models provide the internal characteristics of the environment. The integration of these three elements enables the creation of rich, effective and realistic environments for 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.

TREND

2

Empowering Embodied Decision-Making via Multimodal Large Model

Multi-level end-to-end embodied decision-making: Inspired by multimodal large models, the 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.

TREND

3

Embodied Intelligent Control via Integrating Model Prediction, Reinforcement Learning and Life Sciences

By integrating the dynamic optimization capabilities of model predictive control, adaptive strategies of reinforcement learning, and the redundant multi-loop control mechanisms from life sciences, an embodied intelligent robot control system is constructed to improve the generalization and adaptability of embodied intelligent robot control in dynamic environments.

TREND

4

Generative AI for Embodied Intelligent Robot Design

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 achieves co-optimization of hardware and control strategies in physical simulators, enabling automatic exploration of task-optimal embodied intelligent robot designs.

TREND

5

Highly Synergistic and Dynamically Adaptive Software/Hardware Consistency for Embodied Intelligence

Embodied intelligent robots require consistent software/hardware co-design. By predefining interface specifications of algorithms during hardware development and embedding physical constraints of hardware into algorithm design, system-level consistency and optimization are achieved through joint simulation and validation.

TREND

6

“Manufactory” of Embodied Intelligent Robots

In the simulation 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 rapid design and manufacturing of high-quality embodied intelligent robot systems according to specific performance and requirements.

TREND

7

Large-Scale and High-Quality Dataset for Embodied Intelligence

The construction of large-scale and high-quality datasets for embodied intelligence through physical entity collection and simulation synthesis can enhance embodied intelligent robots’ capabilities in morphological optimization, multimodal training efficiency, and cross-scenario policy transfer.

TREND

8

Advances in Embodied Intelligent Robot Swarms and the Collaboration with Humans

Integrating multi-agent coordination mechanisms to 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’ entry into human society and realize their integration with humans.

TREND

9

Interdisciplinary Open Community for Embodied Intelligent Robots

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

TREND

10

Safety Assessment and Ethical Development for Embodied Intelligent Robots

Through behavior norm verification, decision interpretability analysis, and data 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.