3D Vision-Guided Gripping Systems Research:representing a compound annual growth rate (CAGR) of 6.3% during the forecast period of 2025-2031

QY Research Inc. (Global Market Report Research Publisher) announces the release of 2025 latest report "3D Vision-Guided Gripping Systems- Global Market Share and Ranking, Overall Sales and Demand Forecast 2025-2031". Based on current situation and impact historical analysis (2020-2024) and forecast calculations (2025-2031), this report provides a comprehensive analysis of the global Wire Drawing Dies market, including market size, share, demand, industry development status, and forecasts for the next few years.

The global market for 3D Vision-Guided Gripping Systems was estimated to be worth US$ 1963 million in 2024 and is forecast to a readjusted size of US$ 3011 million by 2031 with a CAGR of 6.3% during the forecast period 2025-2031.

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3D Vision-Guided Gripping Systems Market to Grow at 6.3% CAGR Through 2031

According to the recent report by QYResearch, the global market for 3D Vision-Guided Gripping Systems is experiencing robust growth, with the market size estimated at USD 1.96 billion in 2024 and projected to reach USD 3.01 billion by 2031, representing a compound annual growth rate (CAGR) of 6.3% during the forecast period of 2025-2031. This rapid development is being driven by increased automation in industrial sectors, ongoing advancements in sensor technologies, and the expanding scope of AI-integrated robotic systems.
Leading Companies
Prominent companies operating in the 3D Vision-Guided Gripping Systems market include
ABB
KUKA
FANUC
YASKAWA
Cognex Corporation
Keyence Corporation
Omron Corporation
SICK AG
Basler AG
Zivid
Photoneo
Framos
Datalogic
LMI Technologies
IFM Electronic GmbH
3D Vision-Guided Gripping Systems - Product Summaries
1. Photoneo PhoXi 3D Scanner L
Type: Structured-light 3D scanner
Resolution: up to 3.2 million points
Scanning range: 870-2,150 mm; optimal ~1,239 mm
Scan area at sweet spot: 1,082 × 772 mm
Point-to-point distance: 0.524 mm
Calibration accuracy: 0.200 mm; temporal noise: 0.190 mm
Scan time: 250-2,750 ms; throughput: 16 M pts/s
Dimensions: 77 × 68 × 616 mm; Weight: 1,100 g
2. Cognex InSight L38
Type: 3D vision sensor with embedded AI
Laser options: L3833/L3850/L38100/L38300/L38500
Z repeatability: < 0.5 μm (top) to 10 μm (bottom); Z linearity ±0.04-0.1 % F.S.
Scan frequency: up to 7 kHz (10 kHz with smaller FOV)
Protection: IP65; Operating temp: 0-45 °C; Vibration: 10-57 Hz, 1.5 mm; Shock: 15 G
Weight: 0.94-1.28 kg depending on version
Resolution: 4,096 × 2; Dynamic range: 66 dB
3. MechMind MechEye PRO
Type: Structured-light 3D camera
Accuracy: 0.03 mm @ 0.3 m to 1 mm @ 3 m
Capture time: 0.3-0.9 s depending on model
Baseline options: 80-800 mm depending on version
Dimensions: e.g., 260 × 65 × 142 mm; Weight: 0.7-1.9 kg
Interface: Gigabit Ethernet; Light: blue/red LED or red laser
Operating temp: 0-45 °C; Certifications: CE/FCC/etc.
4. Zivid 2+ M60
Type: Structured-light 3D camera with integrated 2D imaging
Sensor resolution: 5 MP for RGB color + 3D
Working distance: 30-110 cm (optimal ~60 cm)
Field of view: ~570 × 460 mm at 600 mm
Spatial resolution: ~0.24 mm at 600 mm
Capture time: 100 ms to 1 s
Size: 169 × 124 × 56 mm; Weight: ~1,000 g
Durability: IP65, 5 G vibration, 15 G shock, factory-calibrated
5. LMI Technologies Gocator 2610
Type: Laser line 3D profiler
Imager: 9-megapixel; 4,192 points/profile
X-resolution: down to 2.5 μm; Z repeatability: 0.2 μm
Scan rate: up to 10,000 Hz
Measurement range: up to ~475 mm
Applications: semiconductor, battery, electronics inspection
Verified Downstream Customer Names
Mitsubishi Electric
Universal Robots
BOS Innovations
Hänggi GmbH
DHL
JD Logistics
BMW Group
ZF Friedrichshafen AG
Applications and Market Segments
The market is segmented by application into:
Industrial Automation Assembly
Warehouse and Logistics Sorting
Electronics Manufacturing
Food and Packaging Industry
Others
It is also classified by technology type into:
Structured Light-Based 3D Gripping Systems
Laser Scanning-Based 3D Gripping Systems
Stereo Vision-Based 3D Gripping Systems
ToF (Time-of-Flight) Based 3D Gripping Systems
Others
Latest Developments in 2025
In 2025, Photoneo introduced an advanced in-motion hand-eye bag-rack picking system at Automate 2025 in Detroit, aimed at automotive applications. This solution combines real-time 3D scanning with motion compensation algorithms, showcasing the next frontier of flexible automation.
Cognex Corporation also launched the In-Sight L38 in late 2024, which gained momentum in 2025 due to its fusion of 2D and 3D AI-enhanced vision capabilities. It is widely adopted in quality inspection and precise measurement tasks.
Regional Insights
While detailed regional values are pending, the report notes rapid growth across Asia-Pacific, Europe, and North America, driven by manufacturing modernization, rising labor costs, and policy support for smart factories. China, Japan, Germany, the U.S., and South Korea remain primary contributors to both production and consumption.
Market Drivers and Trends
1. Smart Factory Expansion and Industry 4.0 Adoption
Global smart manufacturing investments reached approximately USD 82 billion in 2024 and are projected to increase to nearly USD 90 billion in 2025, growing at around a 9 % CAGR. Manufacturers implementing Industry 4.0 initiatives have reported production output improvements of 10-20 % and reductions in lead times by up to 50 %. High returns on investment-10-15 % capacity gains and 7-20 % productivity improvements-are making smart factory upgrades a key driver of demand for visionguided automation.
2. Labor Shortages Accelerating Robotic Adoption
Many industrialized economies face acute workforce gaps. For example, the U.S. projected a shortage of nearly 450,000 manufacturing workers in 2025, potentially rising to almost 2 million by 2033. To compensate, warehouse and fulfillment centers have accelerated robot usage: Amazon has deployed more than one million warehouse robots, boosting packages handled per employee from 175 to nearly 3,870 and shifting human labor toward higherskill robot supervision roles. Similarly, global robot density in factories reached 162 units per 10,000 employees in 2023-more than double its level seven years earlier-evidencing rapid automation uptake driven by labor constraints.
3. Advances in AI and Real-Time Sensor Fusion
Modern robotics leverage AI and sensor fusion to enable adaptive gripping and intelligent perception. Multi-modal systems combining 3D vision, force sensing, LiDAR, and audio have entered industrial use, enabling real-time quality control and decision-making. Cobots equipped with reinforcement learning have shown error reductions up to 30 % and energy use improvements of 20 %, illustrating how AI-powered vision systems are enabling robots to handle variability in bin picking, assembly, and sorting tasks.
4. Shift Towards Embedded Vision and Edge Processing
As centralized computing gives way to intelligent sensors, 75 % of industrial data processing is expected to occur at the edge by 2025. Edgecapable smart 3D sensor modules reduce latency and bandwidth requirements, enabling live processing of vision data for gripping applications. Projects have demonstrated energy efficiency and downtime reductions of 18-22 % when integrating IoTenabled edge frameworks into factory operations. These embedded solutions allow gripping systems to detect and adapt to changes in real time, greatly improving cycle times and reliability.
5. Increasing Demand for Flexibility and Sustainability
With growing customization and supply chain volatility, manufacturers require flexible automation systems. 2024-2025 trends show a shift toward agile, modular conveyor, cobot, and vision systems that can be rapidly reconfigured. Additionally, many smart factory projects now incorporate environmental objectives: energy use in automated lines can be reduced by 20 % through combined IoT sensing and edge-based analytics, supporting both cost and sustainability goals.
Altogether, the convergence of smart factory investment, workforce pressures, AI-driven sensor fusion, edge intelligence, and sustainability initiatives is creating a powerful momentum behind 3D visionguided gripping systems. These systems not only address labor and efficiency challenges, but also enable nextgeneration automation in flexible, datarich manufacturing environments.
Geopolitical & Trade Considerations
The report warns of potential volatility stemming from the 2025 U.S. tariff adjustments, which may affect global supply chains, capital allocations, and industrial footprints. Companies are advised to strengthen regional resilience and diversify sourcing strategies in light of evolving cross-border dynamics.
The comprehensive analysis combines quantitative forecasts with qualitative insights to guide strategic planning and competitive positioning in the 3D Vision-Guided Gripping Systems space through 2031.
Related Reports:
3D Vision-Guided Gripping Systems - Global Market Share and Ranking, Overall Sales and Demand Forecast 2025-2031
https://www.qyresearch.com/reports/4747610/3d-vision-guided-gripping-systems

Global 3D Vision-Guided Gripping Systems Market Research Report 2025
https://www.qyresearch.com/reports/4747609/3d-vision-guided-gripping-systems

Global 3D Vision-Guided Gripping Systems Sales Market Report, Competitive Analysis and Regional Opportunities 2025-2031
https://www.qyresearch.com/reports/4747608/3d-vision-guided-gripping-systems

Global 3D Vision-Guided Gripping Systems Market Insights, Forecast to 2031
https://www.qyresearch.com/reports/4747607/3d-vision-guided-gripping-systems


The report provides a detailed analysis of the market size, growth potential, and key trends for each segment. Through detailed analysis, industry players can identify profit opportunities, develop strategies for specific customer segments, and allocate resources effectively.

The 3D Vision-Guided Gripping Systems market is segmented as below:
By Company
ABB
KUKA
FANUC
YASKAWA
Cognex Corporation
Keyence Corporation
Omron Corporation
SICK AG
Basler AG
Zivid
Photoneo
Framos
Datalogic
LMI Technologies
IFM Electronic GmbH

Segment by Type
Structured Light-Based 3D Gripping Systems
Laser Scanning-Based 3D Gripping Systems
Stereo Vision-Based 3D Gripping Systems
ToF (Time-of-Flight) Based 3D Gripping Systems
Others

Segment by Application
Industrial Automation Assembly
Warehouse and Logistics Sorting
Electronics Manufacturing
Food and Packaging Industry
Others

Each chapter of the report provides detailed information for readers to further understand the 3D Vision-Guided Gripping Systems market:

Chapter 1: Introduces the report scope of the 3D Vision-Guided Gripping Systems report, global total market size (valve, volume and price). This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry. (2020-2031)
Chapter 2: Detailed analysis of 3D Vision-Guided Gripping Systems manufacturers competitive landscape, price, sales and revenue market share, latest development plan, merger, and acquisition information, etc. (2020-2025)
Chapter 3: Provides the analysis of various 3D Vision-Guided Gripping Systems market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments. (2020-2031)
Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.(2020-2031)
Chapter 5: Sales, revenue of 3D Vision-Guided Gripping Systems in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world..(2020-2031)
Chapter 6: Sales, revenue of 3D Vision-Guided Gripping Systems in country level. It provides sigmate data by Type, and by Application for each country/region.(2020-2031)
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc. (2020-2025)
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.

Benefits of purchasing QYResearch report:

Competitive Analysis: QYResearch provides in-depth 3D Vision-Guided Gripping Systems competitive analysis, including information on key company profiles, new entrants, acquisitions, mergers, large market shear, opportunities, and challenges. These analyses provide clients with a comprehensive understanding of market conditions and competitive dynamics, enabling them to develop effective market strategies and maintain their competitive edge.

Industry Analysis: QYResearch provides 3D Vision-Guided Gripping Systems comprehensive industry data and trend analysis, including raw material analysis, market application analysis, product type analysis, market demand analysis, market supply analysis, downstream market analysis, and supply chain analysis.

and trend analysis. These analyses help clients understand the direction of industry development and make informed business decisions.

Market Size: QYResearch provides 3D Vision-Guided Gripping Systems market size analysis, including capacity, production, sales, production value, price, cost, and profit analysis. This data helps clients understand market size and development potential, and is an important reference for business development.

Other relevant reports of QYResearch:
Global 3D Vision-Guided Gripping Systems Market Research Report 2025
Global 3D Vision-Guided Gripping Systems Sales Market Report, Competitive Analysis and Regional Opportunities 2025-2031
Global 3D Vision-Guided Gripping Systems Market Insights, Forecast to 2031

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