首頁 > 市場調查報告書 > 通訊

人工智能

市場調查報告書

商品編碼

1930695

下一代具身人工智慧機器人通訊網路拓樸結構及晶片產業（2026）

Next-Generation Embodied AI Robot Communication Network Topology and Chip Industry Report, 2026

出版日期: 2026年01月06日 | 出版商:

ResearchInChina | 英文 300 Pages | 商品交期: 最快1-2個工作天內

價格

簡介目錄

具身人工智慧機器人是新一代人工智慧機器人，它將大規模人工智慧模型與實體實體結合，正在實現從 "運算智慧" 到 "物理智慧" 的飛躍。如果將大規模模型比作機器人的“大腦”，那麼通訊網路就可以被視為其“神經系統”。具身人工智慧機器人是高度複雜的分散式系統。它們的 "大腦" 必須在毫秒級的時間內處理來自遍布全身數十個感測器的海量異質數據，並在微秒級的時間內向執行器發出同步指令。

在2026年這個關鍵的轉捩點，ResearchInChina發現，機器人的內外通訊架構正面臨前所未有的重構。傳統的工業機器人通訊架構正接近其物理極限。從 EtherCAT 對 CAN 總線的降維攻擊，到區域架構的實體轉型，再到 NearLink 等新協定的突破，通訊晶片和模組市場蓄勢待發，即將迎來爆發式成長。

本報告探討並分析了具身人工智慧機器人通訊架構的產業鏈，並確定了支援下一代具身人工智慧代理的六大關鍵通訊趨勢。

趨勢一：市場快速成長和晶片專業化預計將使通訊模組市場規模擴大近 100 億元。

隨著具身人工智慧機器人量產在即，通訊鏈路的價值正在經歷從 "通用工業部件" 到 "專用核心組件" 的結構性重組。根據 ResearchInChina 最新預測，該細分市場對通訊模組和專用晶片的需求預計將打破線性成長，進入指數級增長期。

趨勢 2：EtherCAT 解決方案在內部通訊協定中的採用率預計將逐年提高。

長期以來，機器人內部通訊一直處於 "碎片化" 狀態，多種協定並存，包括 USB、CAN 和 RS485。然而，隨著具身人工智慧代理的自由度增加（通常超過 40 個）以及對精確運動控制的需求不斷增長，傳統 CAN 總線的頻寬和即時效能瓶頸日益凸顯。

趨勢 3：網路拓樸結構的重構促使網路拓樸從分散式轉變為區域集中式。

隨著觸覺皮膚和多視角視覺等感測器數量的快速增長，傳統的點對點佈線方式導致機器人內部線束臃腫，造成重量增加和可靠性降低等問題。

趨勢 4：在端對端通訊整合中，I3C 協定正成為解決靈巧手板載互連的關鍵技術。

靈巧手是具身人工智慧機器人中最複雜的末端執行器，需要在極小的空間內整合數十個感測器和馬達。傳統的 CAN 和 UART 介面需要單獨的收發器和晶體振盪器，佔用大量 PCB 面積，且佈線複雜。

趨勢 5：在軟硬體一體化 "資料匯流排" 時代，DDS 和 ROS 2 如何建構分散式神經中樞。

在軟體定義機器人時代，通訊不再只是比特的傳輸，更是資料的分發。 ROS 2 及其底層資料分發服務 (DDS) 將作為預設的基礎通訊中間件，構成機器人的 "智慧中心" 。

趨勢 6：5G-A 和 NearLink 技術的協同作用將支援機器人與雲端、邊緣和終端之間高頻寬、即時的互動。

嵌入式 AI 代理不僅需要強大的“內部神經系統”，還需要靈活的“外部神經系統”來實現雲端、邊緣和終端之間的協作。蜂窩網路（5G-A）和短距離通訊（Wi-Fi/NearLink）有望形成長期的互補共存模式，而不是簡單的相互替代。

具身人工智慧機器人通訊網路概述
具身人工智慧機器人 EtherCAT 通訊網路拓撲概述
EtherCAT 通訊網路技術堆疊
EtherCAT 通訊網路中介軟體
FPGA 晶片和 PHY 晶片在具身人工智慧機器人通訊中的應用
具身人工智慧機器人通訊晶片的產業鍊與規模

第二章：具身人工智慧機器人在各種場景下的通訊應用

感測器通訊架構
運動控制/執行器
靈巧手通訊架構
外部通訊架構
具身人工智慧的發展趨勢機器人通信

第三章主要具身人工智慧機器人本體製造商的通訊網路部署方案

優尼特科技通訊架構
AgiBot通訊架構
KUAVO機器人通訊架構
優必選機器人通訊架構
迪普機器人通訊架構
傅立葉智慧機器人通訊架構
北京人形機器人創新中心通訊架構
上海人形機器人有限公司通訊架構
其他機器人製造商的通訊架構

第四章中國通訊晶片及模組廠商

兆兆半導體
三導科技
惠普半導體
科德菲爾半導體
瑞芯微
摩托車通信
ASIX電子產品
NIIC
吉希半導體
寧信科技
其他中國通訊晶片和模組供應商

第五章：國外通訊晶片與模組供應商

英飛凌
TI
恩智浦
阿爾特拉
瑞薩電子
意法半導體
微晶片
類比元件 (ADI)
安森美
其他國外通訊晶片和模組供應商

簡介目錄

Product Code: WH007

AI Robot Communication Network and Chip Research: Six Evolution Trends and Chip Transformation

Embodied AI robots, namely the new generation of AI robots integrating large AI models and physical entities, are undergoing a leap from "computational intelligence" to "physical intelligence". If large models are the "brain" of robots, then communication networks are their "nervous system". An embodied AI robot is a highly complex distributed system. Its "brain" needs to process massive heterogeneous data from dozens of sensors across its body in milliseconds and issue microsecond-level synchronous commands to actuators.

At the critical node year 2026, ResearchInChina has observed that the internal and external communication architectures of robots are facing unprecedented restructuring. Traditional industrial robot communication architectures have approached physical limits. From the dimension reduction strike of EtherCAT on CAN bus, to the physical transformation of zonal architecture, and then to the breakthrough of new protocols such as NearLink, the communication chip and module market is ushering in a boom period.

The Next-Generation Embodied AI Robot Communication Network Topology and Chip Industry Report, 2026 conducts in-depth research on the industry chain of communication architecture of embodied AI robots. It covers 11 robot manufacturers, 12 Chinese communication module vendors and 13 foreign communication module vendors, and reveals six key communication trends supporting the next-generation embodied AI agents.

Trend 1: In Market Boom and Chip Specialization, Communication Modules Will Witness A Nearly RMB10 Billion Increment.

In the run-up to mass production of embodied AI robots, the value of communication links is undergoing a structural restructuring from "general industrial components" to "specialized core components". According to the latest estimates by ResearchInChina, the demand for communication modules and specialized chips in this market segment will break away from the linear growth track and enter an exponential growth period.

In particular, the EtherCAT Slave Controller (ESC) is emerging as the core incremental driver of this growth. Differing from traditional industrial automation, a humanoid robot has more than 40 joint degrees of freedom, placing a very big demand on the integration and real-time performance of communication nodes.

As shown in the table below, the embodied AI robot dedicated communication market is expected to expand rapidly from USD42 million in 2026 to around USD300 million in 2030.

In addition, FPGA chips are gaining increasing strategic importance in communication links, gradually forming a "FPGA + MCU" heterogeneous collaborative architecture. With its unique parallel processing capability and nanosecond-level low-latency characteristics, FPGAs (such as the Altera Agilex series) are widely used in high-bandwidth multi-sensor fusion, hard real-time industrial bus protocol conversion, and complex motor control loops.

Meanwhile, the market demand for specialized PHY chips (Physical Layer chips) is also surging. Faced with the extremely limited space and heat dissipation challenges inside robot joints, leading vendors represented by Motorcomm and Renesas Electronics are accelerating the launch of Gigabit/2.5G Ethernet PHY chips customized for embodied AI.

These chips are reshaping the physical layer standard of robot internal communication by integrating TSN (Time-Sensitive Networking) clock synchronization features, ultra-low power consumption design, and Wafer-Level Chip Scale Packaging (WLCSP).

Trend 2: Penetration Rate of EtherCAT Solution for Internal Communication Protocol Will Increase Year by Year.

For a long time, robot internal communication has presented a "fragmented" situation where multiple protocols such as USB, CAN, and RS485 coexist. However, with more degrees of freedom of embodied AI agents (usually more than 40) and higher motion control accuracy requirements, the bottlenecks of traditional CAN bus in bandwidth and real-time performance have been fully exposed.

The research by ResearchInChina shows that Ethernet evolving towards automotive Ethernet, especially the EtherCAT protocol, is expected to become a better solution for internal communication integration. EtherCAT is developed by Germany's Beckhoff, and now there have been local companies such as Triductor Technology and HPMicro releasing robot-specific ESC chips authorized by Beckhoff for mass production.

Compared with the "store-and-forward" mechanism of traditional Ethernet, EtherCAT adopts a unique "Processing on the fly" technology. Data frames "fly through" each slave node like high-speed trains, and slave stations can instantly read commands and insert feedback data in nanoseconds without caching. This mechanism enables the EtherCAT system to maintain microsecond-level communication cycles and less than 1 microsecond jitter even when connecting dozens of joints.

In the bipedal walking and balance control of humanoid robots, microsecond-level synchronization of multiple joints is crucial. The Distributed Clocks (DC) technology of EtherCAT can ensure that the synchronization error of all axes is less than 100 nanoseconds, perfectly meeting the requirements for highly dynamic motion control. At present, leading manufacturers including AgiBot, Unitree Robotics, and UBTECH have widely deployed EtherCAT or customized Ethernet-based buses in their flagship products.

Trend 3: Reshaping of Network Topology Leads to A Transition from Distribution to Zonal Centralization.

With the surge in the number of sensors (such as tactile skin and multi-view vision), the traditional point-to-point wiring mode leads to bulky wiring harnesses inside robots, which not only increases weight but also reduces reliability.

Drawing on the evolution of intelligent vehicle E/E architecture, embodied AI robots are accelerating the transformation to "zonal architecture".

Models represented by Tesla Optimus Gen3 and Figure 03 may adopt a Zonal Control Unit (ZCU) design similar to that of automobiles. Sensors and actuators first connect to nearby ZCUs, and then link to the central computing unit via a high-speed Ethernet backbone network. According to measured data from the automotive industry, this design not only significantly reduces the length and weight of wiring harnesses (expected to reduce by 16%-30%) but also lowers assembly difficulty.

Under this trend, the importance of high-speed serial communication technology (SerDes) and TSN (Time-Sensitive Networking) is increasingly prominent. More forward-looking technologies such as the TS-PON all-fiber industrial optical bus proposed by Poncan Semiconductor utilize optical fibers featuring anti-interference, low latency (<10μs) and high bandwidth (above 10Gbps), allowing a single optical fiber to undertake all electrical bus services. It is expected to be put into pilot applications in high-end robot scenarios in the future.

Trend 4: In End Communication Integration, I3C Protocol Is Becoming the Key Technology to Solve Intra-Board Interconnection in Dexterous Hands.

Dexterous hand is the most complex end effector of an embodied AI robot, requiring the integration of dozens of sensors and motors in an extremely small space. Traditional CAN or UART interfaces require independent transceivers and crystal oscillators, occupying large PCB area and complicating wiring.

The I3C (Improved Inter Integrated Circuit) protocol is emerging as the key technology to solve the "last inch" communication problem of dexterous hands.

Compared with the traditional I2C, I3C supports a transmission rate of up to 12.5Mbps (push-pull mode), and In-Band Interrupt (IBI), allowing sensors to actively report emergency data (such as tactile mutations) without additional interrupt lines.

Dexterous hand solutions based on I3C launched by vendors such as NXP show that only two lines are needed to realize communication between the main controller and multiple finger joints. No external PHY chip is required when the main controller integrates an I3C controller, saving a lot of BOM costs and wiring space. Its characteristics of high integration, low power consumption, and hot-swappable support make it an ideal option for high-density tactile sensor arrays and micro-joint control.

Trend 5: For Software-Hardware Integrated "Data Bus", How DDS and ROS 2 Build a Decentralized Nerve Center?

In the era of software-defined robots, communication is not only the transmission of bits but also the distribution of data. ROS 2 and its underlying DDS (Data Distribution Service) as the default underlying communication middleware constitute the "intelligent center" of robots.

DDS adopts a "data-centric" publish-subscribe model, eliminating centralized message brokers and removing single point of failure risks. More importantly, DDS provides extremely rich QoS (Quality of Service) policies, such as reliability, durability, and deadline. This means developers can configure "high-reliability, low-latency" policies for joint control commands, and "best-effort" policies for video streams, thereby realizing efficient scheduling of heterogeneous data in the same network.

Unitree Robotics' G1 robot is a typical representative in this trend. Its internal DDS middleware realizes the decoupling and efficient coordination of motion control, perception, and decision modules, and is even compatible with computing power expansion of external PCs.

Trend 6: Synergy between 5G-A and NearLink Technology Supports Cloud-Edge-Terminal High-Bandwidth Real-Time Interaction for Robots.

Embodied AI agents not only need a robust "internal nervous system" but also an agile "external nervous system" to realize cloud-edge-terminal collaboration. Cellular networks (5G-A) and short-range communications (Wi-Fi/NearLink) will form a long-term complementary coexistence pattern rather than simple substitution.

With 10Gbps downlink rate, millisecond-level latency, and wide-area seamless roaming capability, 5G-A (5.5G) is a must-have option for robots to access the "cloud brain" in mobile scenarios such as outdoor inspections and industrial parks. The Kuavo robot case UBTECH cooperates with China Mobile proves that 5G-A can support high-precision collaboration of multi-robot groups and real-time ultra-high-definition video backhaul.

In the field of short-range communication, China's independently developed NearLink technology shows great potential to replace Wi-Fi and Bluetooth. The NearLink SLB mode features microsecond-level air interface latency (20μs) and nanosecond-level synchronization accuracy, and supports concurrent connections of up to 4096 nodes. This enables NearLink to be competent for external communication, but also at the joint connections of non-metallic skins, it is even expected to try wirelessly replacing some signal cables to explore the solution to the sore point of mechanical wear. At present, among Chiense companies, Triductor Technology has launched NearLink products targeting embodied AI robots.

1 Embodied AI Robot Communication Network Topology

1.1 Overview of Embodied AI Robot Communication Networks
Overview of Embodied AI Robot Communication Network Modules
Overview of Embodied AI Robot Communication Networks
Multi-modal Data for Internal Communication of Embodied AI Robots
EtherCAT Network Topology of Humanoid Robots
Requirements of Embodied AI Robots for Internal Communication Transmission (1)
Requirements of Embodied AI Robots for Internal Communication Transmission (2)
Ethernet Is Expected to Become the Unified Standard for Communication Protocols
1.2 Overview of EtherCAT Communication Network Topology for Embodied AI Robots
Overview of EtherCAT
EtherCAT "Fly-by" Processing Mechanism
EtherCAT Station State Machine Management Mechanism
EtherCAT Time Synchronization Technology
Application of EtherCAT High-precision Synchronization Mechanism in Embodied AI
EtherCAT Operation Principle
Implementation Mode of EtherCAT Slave Station System
Adaptability of EtherCAT to Embodied AI Robots
Comparison Between EtherCAT and CAN Bus
Advantages and Trends of EtherCAT Communication Protocol
Defects and Challenges of EtherCAT Communication Protocol
Next-generation EtherCAT Technology
1.3 EtherCAT Communication Network Technology Stack
ROS 2 Communication Architecture Technology Stack
New Features of ROS 2
Core Components of ROS 2 System
Communication Architecture Design of ROS 2
ROS 2-Based Communication Architecture of Embodied AI Robots
Example of Data Processing Flow Based on ROS 2 System Architecture
ROS 2 Robot Endpoint Communication Solution
Partial Applications of ROS 2 in Embodied AI Robots
1.4 EtherCAT Communication Network Middleware
Overview of DDS
Core Models and Advantages of DDS
QoS Policies of DDS
1.5 Application of FPGA Chips and PHY Chips in Embodied AI Robot Communication
Overview of Ethernet Physical Layer Chips (PHY)
Application of Ethernet Physical Layer Chips (PHY)
Core Advantages of FPGA in Robot Control and Communication Systems
Practical Application Cases of FPGA in Robotics
Application of FPGA in Communication of Tesla Optimus Gen 2
1.6 Industry Chain and Scale of Communication Chips for Embodied AI Robots
Underlying Hardware Industry Chain of Internal Communication Units for Embodied AI Robots
Industry Chain Structure of External Communication for Embodied AI Robots
Internal Communication Cost of Embodied AI Robots
Global Embodied AI Robot Communication Module Market Size, 2026E-2030E
China Embodied AI Robot Communication Module Market Size, 2026E-2030E

2 Application of Communication in Various Scenarios of Embodied AI Robots

2.1 Sensor Communication Architecture
Types of Sensors Equipped on Embodied AI Robots
Robot CMOS Image Sensor Communication
Robot LiDAR/Radar Communication
Microphone Network Communication of Embodied AI Robots
EtherCAT-based Machine Vision System Integration Technology
EtherCAT-based Machine Vision System Framework
2.2 Motion Control and Actuators
Motion Control Communication Network Module and Application of Embodied AI Robots
Communication Interface Design of Embodied AI Robots
Hardware Architecture Analysis of Actuator and EtherCAT Communication Network for Embodied AI Robots
EtherCAT Has Significant Advantages in Robot Motion Control
2.3 Dexterous Hand Communication Architecture
Types and Considerations of Dexterous Hand Communication
Dexterous Hand Communication Architecture
Dexterous Hand Palm Board EtherCAT Slave Station System
Challenges of Dexterous Hand Distributed Communication Architecture
Differences Between I3C and I2C and Their Advantages in Embodied AI
Dexterous Hand Distributed Communication Architecture Based on I3C Bus
2.4 External Communication Architecture
External Communication Technology Is the Foundation of Embodied AI Robots
Comparison Between Wireless and Wired Communication of Embodied AI Robots
External Communication Is Led by Wireless Communication
Application of Cellular Network in External Communication of Embodied AI Robots
Application of Wi-Fi and Other Local Area Networks in External Communication of Embodied AI Robots
Introduction to NearLink Technology
Application of NearLink in External Communication of Embodied AI Robots
2.5 Development Trends of Embodied AI Robot Communication
Current Development Requirements for Precision and Latency in Humanoid Robot Motion Control
TS-PON New-generation All-Fiber Industrial Optical Bus Technology
TS-PON All-Optical Network Chip Robot Communication Architecture
Paradigm Shift of Internal Control Network from "Distributed Functional Control" to "Zonal Centralized Control"
Application of Time-sensitive Networking (TSN) Ethernet
Architectural Innovation of TSN in Robot Communication
Application Advantages of 5G-Advanced (5G-A) in Industrial Scenarios of Embodied AI Robots
Advantages of NearLink Technology in Embodied AI Robots
In-depth Optimization of DDS Middleware and ROS 2
Migration of New-generation High-speed Serial Communication Technology to Robots

3 Communication Network Deployment Schemes of Major Embodied AI Robot Body Manufacturers

3.1 Unitree Technology Communication Architecture
Unitree Humanoid Robot G1
Software System Architecture of Unitree G1
Dual-SoC Communication Architecture of Unitree G1
Communication Parameters of Main Control Chip
Communication Parameters of Joint Control Chip
Internal Network Architecture and Topology
Internal Bus and Actuator Communication
Sensor Communication Path
Physical Communication Interface Matrix (G1-Edu)
Overview of Unitree G1 Communication Interfaces
GPIO / Serial Bus Expansion Interfaces
Core Technical Feature - Real-time Data Distribution Based on DDS
Unitree Quadruped Robot Go2
Main Control Board Module Layout of Unitree Go2
Overview of Main Control Board Communication Module of Unitree Go2
Overview of Wireless Communication Module of Unitree Go2
Detailed Composition of Wireless Communication Module of Unitree Go2
Parameters and Functions of Wireless Communication Module of Unitree Go2
Communication Interface of Unitree Go2
Multi-protocol Communication of Unitree Go2
Core Communication Technologies of Unitree Go2 (1)
Core Communication Technologies of Unitree Go2 (2)
3.2 AgiBot Communication Architecture
Communication Architecture of AgiBot Lingxi X1
Whole-machine Wiring of AgiBot Lingxi X1
Whole-machine Circuitry of AgiBot Lingxi X1
Core Communication Module DCU
Execution Layer Communication Architecture
Communication Parameters of Joint Motors
3.3 KUAVO Robot Communication Architecture
Application of 5G-A Technology in KUAVO Robots
Lower Computer Communication Configuration of KUAVO 5 MAX
Upper Computer Parameter Configuration of KUAVO 5 MAX
Dexterous Hand and Sensor Communication Configuration of KUAVO 5 MAX
New-generation Leju KUAVO Robot Adopts NVIDIA Jetson Thor Communication Configuration
3.4 UBTECH Robot Communication Architecture
Communication Parameters of UBTECH Robots
Actuator Communication Network Architecture of UBTECH Robots
Sensor Communication Network Architecture of UBTECH Robots
UBTECH Robot BrainNet 2.0
External Communication Architecture of UBTECH Robots
Application of UWB Positioning Technology in UBTECH Robots
3.5 DEEP Robotics Robot Communication Architecture
Joint Communication Configuration of DEEP Robotics J Series Robots
Configuration Parameters of DEEP Robotics Jueying X20 Robot
Configuration Parameters of DEEP Robotics Jueying Lite3 Robot
External Communication Application of DEEP Robotics Lynx M20
3.6 Fourier Intelligence Robot Communication Architecture
Basic Parameters of Fourier Robots
Communication Architecture of Fourier Robot N1
Partial Communication Bill of Materials of Fourier Humanoid Robot Fourier N1
Electrical Architecture of Fourier Robot GR-1
Electrical Architecture Disassembly of Fourier Robot GR-1
3.7 Beijing Innovation Center of Humanoid Robotics Communication Architecture
Communication Architecture Parameters of Tiangong 2.0
Communication Capabilities of Cerebrum and Cerebellum Modules of Tiangong 2.0
Dexterous Hand and Actuator Communication Architecture of Tiangong 2.0
Sensor and Voice Module Communication Architecture of Tiangong 2.0
Communication Architecture Parameters of Tianyi 2.0
3.8 Humanoid Robot (Shanghai) Co., Ltd. Communication Architecture
Perception and Control System Design of "Qinglong"
Communication Architecture of "Qinglong" Robot
Motion Control Computer Communication Architecture of "Qinglong"
Arm and Actuator Communication Architecture of "Qinglong"
Communication Device Execution Layer of "Qinglong"
3.9 Communication Architectures of Other Robot Manufacturers
Tesla EtherLoop High-speed Bus Technology
External Communication Configuration of Tesla Optimus
Communication System of Xiaomi CyberOne
Communication System Architecture of Xiaomi CyberOne
Communication Parameters of LimX Dynamics LimX Oli Robot
Communication Interfaces of LimX Dynamics LimX Oli Robot

4 Chinese Communication Chip and Module Vendors

4.1 GigaDevice Semiconductor
Robot Chip Product Layout
Robot Internal Communication Network Chips (1)
Robot Internal Communication Network Chips (2)
Joint Control Chips
EtherCAT Servo Slave Station Solution
High-performance MCUs
Coreless Motor Solutions
4.2 Triductor Technology
Communication Chip Products and Solutions
Cooperation in the Field of Embodied AI Robots
EtherCAT Extension Technology Layout
EtherCAT Slave Station Control Chips
NearLink Chip Series
4.3 HPMicro Semiconductor
Humanoid Robot Product Layout (1)
Humanoid Robot Product Layout (2)
Robot Joint-specific Chip Modules
HPM6E8Y-based Joint Motor Driver Solution
MCUs Suitable for Robot Hands
MCUs Suitable for Robot Joints
4.4 Codefair Semiconductor
EtherCAT Slave Station Controller Chips
Series Working Modes
Series Chips (1)
Series Chips (2)
4.5 Rockchip
Strategic Layout in Robot Industry
EtherCAT Bus: Real-time Ethernet Communication Solution for Robots
Specialized Robot SDK and Grouped Development Board Platform
High-performance SOCs (1)
High-performance SOCs (2)
EtherCAT Multi-axis Motion Control Solution
4.6 Motorcomm
Robot PHY Chip Layout
Gigabit Ethernet Physical Layer Chips
Single-port 2.5G Ethernet Physical Layer Chips
4.7 ASIX Electronics
Industrial Ethernet Chips (1)
Industrial Ethernet Chips (2)
Robot Arm Solutions
Industrial Ethernet Chips (3)
Self-developed Master Station Software Protocol Stack
4.8 NIIC
Core Communication Technologies for Embodied AI
NIIC Participated in the Drafting of Embodied AI Communication Standards
Cooperation with Intel on Embodied AI Controllers
Embodied AI Cerebrum and Cerebellum Network Configuration
Flagship Embodied AI Cerebrum and Cerebellum Network Configuration
4.9 Geehy Semiconductor
Robot Main Control + Communication Module Solution
High-precision Encoder-specific MCUs
Bus-type Low-voltage Servo Solutions
Main Control Chips
Motor Control SoCs
4.10 Nsing Technologies
Embodied AI Robot Product Layout
Embodied AI Robot Product Layout - Communication Performance Overview
Drive Module Gateway Chips
Joint Drive Module Chips
Dexterous Hand Drive Chips
4.11 Other Chinese Communication Chip and Module Vendors
Quectel's AI Modules
Quectel's Edge Computing-enabled Development Boards and Multi-modal Handheld Terminals
Meig Smart Technology's Industry-grade Edge AI BOX Solutions