Edge Computing Robotics Hardware Market Size, Share, Opportunities, and Trends Report Segmented By Hardware Component, End User, and Geography – Forecasts from 2025 to 2030

Description

Edge Computing Robotics Hardware Market Size:

The Edge Computing Robotics Hardware Market is expected to grow at a significant CAGR during the projected period.

The edge computing robotics hardware market is the area engaged in processes related to the development and deployment of hardware systems to impart edge computing capabilities to robotic platforms. Edge computing in robotics means that data is collected and processed locally on or near the robotic device itself, rather than being entirely reliant on resources that exist within the cloud. This local processing decreases latency, allows for real-time decision-making, improves reliability, enhances data privacy, and reduces bandwidth requirements. The market for edge-computing robotics hardware is rapidly expanding due to AI and robotics merging and growing demand for low-latency real-time processing and industrial automation.

Additionally, the need for localized data processing is driving this growth, wherein robots act as intelligent nodes performing edge analytics without the dependence on centralized servers. This helps in abating privacy and security issues so that industries such as healthcare or defense can comply with privacy regulations while not compromising operational efficiency. With a further enhancement coming from technology advancements in hardware architecture, such as energy-efficient processors, special AI accelerators, and miniaturized computing units, which are also advancing in decreasing power consumption, it is expected to boost the market growth during the projected period.

Edge Computing Robotics Hardware Market Overview & Scope

The Edge Computing Robotics Hardware Market is segmented by:

• Hardware Component: The processors segment is expected to hold a significant share in the market. Processors, which include CPUs, GPUs, and other processors, are needed for AI model inference, providing real-time data processing and autonomous decision-making directly onto robotic edge devices. They strike a balance between computing performance, power efficiency, and cost while supporting computation-intensive tasks like image recognition, speech processing, and predictive analytics in robotics, which is leading to an increase in its demand globally.
• End User: The consumer electronics segment constitutes the major part of the market because of the increasing adoption of smartphones, smart home appliances, and wearable devices, all relying heavily on edge computing robotics hardware for local processing. Meanwhile, the automotive segment is posited to become the fastest-growing segment, capitalizing on rapid advances in autonomous driving, in-vehicle AI processing, and connected car technologies requiring low-latency real-time edge processing in robotics and AI systems.
• Region: North America is expected to witness the fastest growth in the edge computing robotics hardware market owing to the presence of leading-edge technology companies, rapid developments in AI chip developments, early adoption of edge computing in sectors such as automotive, health care, manufacturing, and smart cities, aside from this increase in government initiatives is also boosting the market expansion.

Top Trends Shaping the Edge Computing Robotics Hardware Market

1. AI-Powered Edge Hardware
   AI chips and accelerators are increasingly integrated into robotics hardware for enabling real-time decision making along with on-device processing of data with fast inference without depending on a central cloud. Hardware devices, such as NVIDIA Corporation's Jetson AGX Xavier, provide AI performance with energy efficiency for edge computing in logistics robots.
2. Energy Efficiency and Sustainability
   The rise in sustainability and energy efficiency trends across the sectors is leading to developers designing low-power edge computing hardware for robotics, which provides energy optimization. Efficient edge computing robotics hardware can work to decrease overall power consumption, along with more eco-friendly robotics deployment for diverse operations.

Edge Computing Robotics Hardware Market Growth Drivers vs. Challenges

Drivers:

• Growing Proliferation of IoT devices and Integration with Emerging Technologies: Connected-IoT robots generate a large amount of data. Edge hardware processes such information near the source, thereby reducing bandwidth requirements and allowing for seamless integration with 5G, artificial intelligence/machine learning (AI/ML), and swarm robotics. This begins the adoption of multi-robot collaboration in which robots share real-time insights to carry out activities such as search-and-rescue or assembly lines, which is expected to promote the requirement for edge computing hardware in robotic applications.
• Rise in demand in Industrial automation & logistics: Increase in automation at a wide scale across warehousing, intralogistics, discrete manufacturing, and AGV/AMR deployments makes for a rise in labor substitution, throughput gains, and uptime. These applications are increasingly investing in more capable on-site edge hardware to maximize robot autonomy, along with predictive maintenance, local analytics. Task robot investments bring in more funding for hardware adoption.

Additionally, the increase in demand for on-device AI interface for robots is growing to navigate through detection of objects, safety, along with optimizing route, which is supporting the deployment of edge computing hardware such as edge AI chips, modules, and servers in the logistics industry. For instance, InvenSense's 6-axis family of motion sensors embedded with processors provided by TDK corporation, which provides applications in robotics.

Challenges:

• Limited Computing and Storage Resources: Most edge devices still have limited hardware, such as an MCU processor, making it challenging to execute complex AI models on these devices without heavy optimization. This means compromising performance, especially on battery-powered robots, where model quantization or pruning can take several months. This can hamper the adoption of the market across the industries globally.

Edge Computing Robotics Hardware Market Regional Analysis

• India: India is witnessing growth as an emerging market fueled by electronics manufacturing, 5G adoption, IoT expansion, and programs such as Digital India, which will generate increased demand for edge AI hardware used in robotics. Moreover, the country installed 8,510 new robots in 2023, which is a 59 percent increase from previous years as per IFR data.
• United States: The United States market is growing at a significant pace driven by the increase investment in automation and robotic adoption across diverse industries and increase in government initiatives and funding for growth in the edge computing technology which is expected to promote its application in robotics and adoption among diverse sectors of the country.

Edge Computing Robotics Hardware Market Competitive Landscape

The market is fragmented, with many notable players, including NVIDIA Corporation, Intel Corporation, Advanced Micro Devices, Inc., Qualcomm Technologies, Inc., SiMa Technologies, Inc., Midea Group, TDK Corporation, Renesas Electronics Corporation, among others.

• Product Launch: In February 2024, A single-chip RZ/V2H MPU for next-generation robotics was introduced by Renesas Electronics, envisioned with vision AI and real-time control capabilities. Compared with 1 TOPS/W from older products, the new-generation AI accelerator, DRP-AI3 (Dynamically Reconfigurable Processor), can efficiently operate at 10 TOPS/W. The device is a vision A.I. real-time control system and is capable of advanced AI inference operations up to 80 TOPS without any cooling fans. The extension of Renesas' RZ Family of microprocessors targets high-performance robotic applications.
• Program Launch: In June 2024, TDK Corporation announced the launch of the InvenSense Sensor Partner Program to fast-track the time to commercial applications and innovations in IoT, wearables, AR, VR, and robotics fields. The program enables ODMs, OEMs, developers, engineers, and tech enthusiasts to collaborate using a variety of InvenSense MEMS sensors, including those for motion, industrial motion modules, microphones, pressure, and ultrasonic sensing in the above fields.

Edge Computing Robotics Hardware Market Scope:

Edge Computing Robotics Hardware Market Segmentation:

• By Hardware Component
  • Sensors
  • Processors
  • Others
• By End-User
  • Healthcare
  • Consumer Electronics
  • Manufacturing
  • Warehousing and Logistics
  • Automotive
  • Others
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • UAE
    • Others
  • Asia Pacific
    • Japan
    • China
    • India
    • South Korea
    • Taiwan
    • Others

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Table Of Contents

1. EXECUTIVE SUMMARY

2. MARKET SNAPSHOT

2.1. Market Overview

2.2. Market Definition

2.3. Scope of the Study

2.4. Market Segmentation

3. BUSINESS LANDSCAPE

3.1. Market Drivers

3.2. Market Restraints

3.3. Market Opportunities

3.4. Porter's Five Forces Analysis

3.5. Industry Value Chain Analysis

3.6. Policies and Regulations

3.7. Strategic Recommendations

4. TECHNOLOGICAL OUTLOOK

5. EDGE COMPUTING ROBOTICS HARDWARE MARKET BY HARDWARE COMPONENT

5.1. Introduction

5.2. Sensors

5.3. Processors

5.4. Others

6. EDGE COMPUTING ROBOTICS HARDWARE MARKET BY END-USER

6.1. Introduction

6.2. Healthcare

6.3. Consumer Electronics

6.4. Manufacturing

6.5. Warehousing and Logistics

6.6. Automotive

6.7. Others

7. EDGE COMPUTING ROBOTICS HARDWARE MARKET BY GEOGRAPHY

7.1. Introduction

7.2. North America

7.2.1. United States

7.2.2. Canada

7.2.3. Mexico

7.3. South America

7.3.1. Brazil

7.3.2. Argentina

7.3.3. Others

7.4. Europe

7.4.1. United Kingdom

7.4.2. Germany

7.4.3. France

7.4.4. Italy

7.4.5. Others

7.5. Middle East & Africa

7.5.1. Saudi Arabia

7.5.2. UAE

7.5.3. Others

7.6. Asia Pacific

7.6.1. Japan

7.6.2. China

7.6.3. India

7.6.4. South Korea

7.6.5. Taiwan

7.6.6. Others

8. COMPETITIVE ENVIRONMENT AND ANALYSIS

8.1. Major Players and Strategy Analysis

8.2. Market Share Analysis

8.3. Mergers, Acquisitions, Agreements, and Collaborations

8.4. Competitive Dashboard

9. COMPANY PROFILES

9.1. NVIDIA Corporation

9.2. Intel Corporation

9.3. Advanced Micro Devices, Inc.

9.4. Qualcomm Technologies, Inc

9.5. SiMa Technologies, Inc

9.6. Midea Group

9.7. TDK Corporation

9.8. Renesas Electronics Corporation

10. APPENDIX

10.1. Currency

10.2. Assumptions

10.3. Base and Forecast Years Timeline

10.4. Key benefits for the stakeholders

10.5. Research Methodology

10.6. Abbreviations

Companies Profiled

NVIDIA Corporation

Intel Corporation

Advanced Micro Devices, Inc.

 Qualcomm Technologies, Inc

SiMa Technologies, Inc

Midea Group

TDK Corporation

Renesas Electronics Corporation

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