
- Get in Touch with Us
Last Updated: Apr 25, 2025 | Study Period:
a system-on-chip architecture with outstanding performance for direct tracking in SLAM. Abstract: A series of algorithms known as simultaneous localization and mapping, or SLAM, addresses the challenge of determining an observer's position in an uncharted environment while creating a map of that environment.
SLAM is a project that helps software engineers create interfaces and software that guarantee accurate and dependable operation by ensuring that software satisfies important behavioural properties of the interfaces it utilises.
SLAM is a crucial component of robotics that assists robots in estimating their pose, or the location and orientation on the map, as they build an environment map to perform autonomous tasks.
An algorithm known as simultaneous localization and mapping (SLAM) combines information from your mapping system's onboard sensors, such as lidar, an RGB camera, an IMU, and others, to calculate your trajectory as you move through an asset.
However, SLAM can be expensive to compute and may have problems when dealing with large maps or a drop in sensor data sampling rate. Position and orientation are determined through inertial navigation using information from inertial measurement units (IMU).
Simultaneous Location and Mapping (SLAM) has recently become a focus of research in the area of intelligent robots. The visual image serves as its processing subject. The application of deep learning to computer vision has seen considerable success, making the combination of deep learning with slam technology a workable idea.
The Global slam on-chip market accounted for $XX Billion in 2023 and is anticipated to reach $XX Billion by 2030, registering a CAGR of XX% from 2024 to 2030.
With the arrival of the newest ZEB family member, even more people may now access SLAM on chip at a cheaper cost.However, it is already providing cost-effective 3D data for some of the biggest construction companies in the world thanks to new components and the smartest SLAM.
The ZEB Go allows users to quickly build 2D and 3D digital models independent of expertise or technical surveying skill. It is designed for usage in indoor and underground areas.
Smaller surveyors and blue chip companies alike are swarming to incorporate SLAM into their enterprises. SLAM is on the cusp of becoming a mainstream product in the toolkits of every major organisation, whether it's to build 2D floor plans of warehouses or a 3D model of a mine shaft.
Sl no | Topic |
1 | Market Segmentation |
2 | Scope of the report |
3 | Abbreviations |
4 | Research Methodology |
5 | Executive Summary |
6 | Introduction |
7 | Insights from Industry stakeholders |
8 | Cost breakdown of Product by sub-components and average profit margin |
9 | Disruptive innovation in the Industry |
10 | Technology trends in the Industry |
11 | Consumer trends in the industry |
12 | Recent Production Milestones |
13 | Component Manufacturing in US, EU and China |
14 | COVID-19 impact on overall market |
15 | COVID-19 impact on Production of components |
16 | COVID-19 impact on Point of sale |
17 | Market Segmentation, Dynamics and Forecast by Geography, 2023-2030 |
18 | Market Segmentation, Dynamics and Forecast by Product Type, 2023-2030 |
19 | Market Segmentation, Dynamics and Forecast by Application, 2023-2030 |
20 | Market Segmentation, Dynamics and Forecast by End use, 2023-2030 |
21 | Product installation rate by OEM, 2023 |
22 | Incline/Decline in Average B-2-B selling price in past 5 years |
23 | Competition from substitute products |
24 | Gross margin and average profitability of suppliers |
25 | New product development in past 12 months |
26 | M&A in past 12 months |
27 | Growth strategy of leading players |
28 | Market share of vendors, 2023 |
29 | Company Profiles |
30 | Unmet needs and opportunity for new suppliers |
31 | Conclusion |
32 | Appendix |