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JIANGSU TG SECURITY TECHNOLOGY CO., LTD
TG security
Currently, the global embodied intelligence technology is showing an accelerated evolution trend, with breakthroughs in five dimensions of perception interaction, decision-making cognition, control execution, virtual real domain data fusion, and system integration, which are driving embodied intelligence from the laboratory to large-scale applications.
One is the embedding of world models and the transition of perception interaction. Driven by the world model and multimodal perception technology, embodied intelligence has significantly improved its ability to understand and interact with physical environments, achieving a paradigm shift from "stimulus response" to "deductive decision-making" and from data restructuring to pattern understanding. Meta has launched the V-JEPA2 world model, which can predict the consequences of different behaviors and rank them based on their goals, greatly improving the accuracy of actions. Peking University has proposed an MLA multi sensory language action model architecture, which introduces a complete multi sensory modality and provides more reliable decision-making basis by integrating heterogeneous signals.
Secondly, there is an end-to-end trend and a paradigm shift in decision-making. The hierarchical decision-making architecture of embodied intelligence "brain+cerebellum" has matured and is increasingly being applied; The end-to-end model, with its advantages of wide coverage, low latency, high autonomy, and strong collaboration, has shown great potential in the exploration of embodied intelligence towards general generalization. Google DeepMind's Gemini Robotics relies on an end-to-end VLA architecture and has excellent cross ontology generalization ability; The DOBOT-VLA model independently developed by Yuejiang in China integrates visual, linguistic, and control capabilities, and has been optimized through real-world reinforcement learning. Equipped with its humanoid robot ATOM, it has achieved mass production in 2025 and can complete complex tasks such as walking, dynamic balancing, and precision assembly.
Thirdly, breakthroughs in flexible materials have led to the emergence of self-healing capabilities. The material revolution is driving the evolution of embodied intelligence from "rigid execution end" to "intelligent adaptation ontology". The skin like tactile sensor and electronic skin enable embodied intelligence to have highly sensitive environmental perception capabilities, while the biomimetic flexible structure endows embodied intelligent life forms with multimodal motion capabilities such as crawling, rolling, and peristalsis, effectively adapting to and expanding application scenarios. Self repairing materials achieve active self-healing breakthroughs. After the body is damaged, it can achieve reversible recombination of chemical bonds under the action of light and heat. It integrates damage detection, localization, and self-healing functions, greatly improving the durability and reliability of embodied intelligence in complex and harsh environments, ensuring long-term autonomous operation.
The fourth is the integration of virtual and real data, and the unification of data standards. The high cost and small scale of real machine data collection, as well as weak generalization ability to unseen environments, have become bottlenecks in the development of embodied intelligence. The generative data source is a simulation environment created from the big model, with a large volume and high degree of structure, which can fill the data gap at low cost. Combined with physical law constraints and mixed data paradigms, and calibrated with real machine data, it can significantly narrow the gap between simulation and reality. Domestic enterprise 51Sim has accumulated end-to-end assisted driving scenarios and synthesized data based on the Nvidia platform, successfully used for robot training in complex scenarios such as ports and mines. The "Dome DOME" platform unifies data interfaces and format specifications, breaks down data silos, builds a universal language for the industry, and effectively promotes cross scenario interoperability and high-quality data supply.
At present, China's embodied intelligence is in a critical stage of coordinating technological breakthroughs, industrial introduction, and ecological cultivation. The localization of core hardware has accelerated, and the performance of large models has been greatly enhanced. Domestic computing power can efficiently carry complex models, and preliminary application capabilities have been formed in some fields. But with the increasingly fierce international competition, the deep challenges of embodied intelligence cannot be ignored.
Firstly, the autonomous controllability of core components needs to be improved, with high external dependence on servo motors, reducers, and high-end sensors. The endurance of the energy system is insufficient, and there are still weaknesses in the full stack self-developed capability; Secondly, the standard system and industrial ecosystem still need to be improved, with inconsistent hardware interfaces, communication protocols, and software compatibility standards, widespread data silos, limited influence of open source communities, and insufficient supply of high-quality interactive data; Thirdly, the security governance system still needs to be improved, and the division of responsibility for autonomous system accidents is difficult to define. Continuous collection of sensitive data can easily lead to risks such as data leakage and privacy infringement, and the trustworthy mechanism for cross institutional collaboration needs to be improved.
In the face of the above challenges, China should seize the development window period, take independent innovation as the core, standard construction as the starting point, and safety governance as the bottom line, accelerate the cultivation of a embodied intelligent industrial ecology, and inject strong momentum into the development of new quality productivity and the construction of a strong technological country.
One is to strengthen the layout of strategic technological forces and consolidate the foundation of independent innovation. Relying on the new national system, we will strengthen the strategic scientific and technological capabilities of national key laboratories in the field of embodied intelligence, and carry out organized scientific research around cutting-edge directions such as the "information physics cognition" three domain fusion model, end-to-end decision-making architecture, and biomimetic flexible materials. Deepen the integration of industry, academia, and research led by enterprises, support leading technology enterprises to take the lead in forming innovation consortia, concentrate advantageous resources to break through the bottleneck of localization of core components such as servo motors, reducers, and planetary roller screws, connect the entire chain of "basic research technology development industrial application", and break through the shackles of industrial development from the source.
The second is to build an open and collaborative industrial ecosystem, leading high-quality development with high standards. Accelerate the development of cross industry hardware interfaces, communication protocols, and software compatibility standards, and promote independent and controllable basic software such as operating systems and middleware. Explore the establishment of high-level data aggregation and governance entities, develop multimodal data collection and annotation standards, build simulation benchmarks and data open platforms for key scenarios such as intelligent manufacturing and high-risk operations, and break down barriers to data circulation. Vigorously cultivate a local open source ecosystem, encourage universities, research institutes, and enterprises to jointly build algorithm computing power sharing systems, lower research and development barriers, accelerate technological iteration, and lead industry quality upgrading with high-level standardization and open source.
The third is to establish a sound security governance system and build a solid foundation for trustworthy development. Build a hierarchical protection mechanism that covers algorithm, data, and physical security, clarifying the boundaries of rights and responsibilities of all parties involved in production, use, algorithm supply, and supervision. Forward looking research on accident liability determination, cross institutional collaboration and mutual trust governance rules, and safety and ethical guidelines for specific navigation, group collaboration, and other behaviors. Explore inclusive and prudent regulatory models, conduct full lifecycle safety ethics assessments, establish proactive and secure defense systems in depth, and provide institutional guarantees for the large-scale implementation and long-term healthy development of embodied intelligence.
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