Sensor technologies

Global Automated Guided Vehicle Sensor Technologies Market

Dublin, March 31, 2021 (GLOBE NEWSWIRE) – The report ‘Growth Opportunities in Sensor Technologies for Automated Guided Vehicles’ has been added to offer.

AGVS streamlines order fulfillment tasks in logistics centers and improves safety in production lines. AGVs can do more than material handling, such as scanning barcodes and transferring the scanned data to the central cloud system. AGVs automate all material handling tasks and eliminate the need for workers to move materials with the operating facility. Therefore, investing in AGVs will increase the ROI rate in 2-3 years. Large logistics companies accelerate ROI because these companies handle thousands of deliveries every day.

The AGV market is highly fragmented with many market leaders and startups. Partnerships between these two parties are quite frequent. For example, the developer of AGV has partnered with cutting edge technology startups to improve the functionality of AGVS. Advanced AGVs use both sensors and AI to autonomously navigate the facility without human guidance.

Main topics covered:

Chapter 1: Strategic imperatives
1.1 The strategic imperative
1.2 Impact of the three main strategic imperatives of AGVs
1.3 About the Growth Pipeline Engine
1.4 Growth Opportunities Fuel the Growth Pipeline Engine
1.5 Research process and methodology
1.6 Main conclusions

Chapter 2: Technology Landscape: Role of Sensors, AI and Mobile Manipulators in AGVs
2.1 Automated guided vehicles are suitable for handling raw materials for ongoing manufacturing scenarios
2.2 AGV: Technological landscape
2.3 Sensor Technology Trends Associated with AGVs – Key Sensor Technologies and Suppliers for AGVs
2.4 The COVID-19 pandemic accelerated the implementation of the mobile manipulator in e-commerce order fulfillment and industrial operations
2.5 AGV Patent Trends: US Leading the World in Patent Filing

Chapter 3: Role of Computer Vision and Machine Learning in Automated Guided Vehicles
3.1 AI powers AGVs to help optimize production
3.2 Machine learning and deep learning enhance AGV’s capabilities
3.3 Computer / machine vision applications in AGVs: continuous movement of objects without human intervention
3.4 Applications of computer / machine vision in AGVs for barcode reading, inspection, monitoring and security

Chapter 4: Businesses in Action: Key AGV Developers
4.1 Key participants
4.2 AI companies working on robotic vehicle development focusing on artificial intelligence aspects

Chapter 5: Use cases
5.1 Use case 1: Micron Technology, USA
5.2 Use case 2: BMW, Germany
5.3 Use case 3: Universal Robots, Denmark, and Unilever, Poland

Chapter 6: Growth opportunities
6.1 Growth opportunity 1: Warehouse automation for inventory management
6.2 Growth opportunity 2: Leverage safety and optimize costs in production facilities

Chapter 7: Key Contacts

Companies mentioned

  • Bmw
  • Micron Technology, United States
  • Unilever
  • Universal robots

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