Advanced Sensors, Artificial Intelligence and Machine Learning encourage AGV Development
AGVS streamlines tasks in order fulfillment in logistics centers as well as improve safety in production lines. AGVs can perform more than material handling such as scanning barcodes and transferring the scanned data to the central cloud system. AGVs automate all the material handling tasks and remove the need for having workers move materials with the operation facility. Therefore, investment in AGVs will increase the rate of ROI in 2 to 3 years. Large logistics companies accelerate ROI since these companies handle thousands of deliveries every day.
AGV market is highly fragmented with many market leaders and startups. Partnerships between these two parties are quite common. For example, the developer of AGVs partnered with deep tech startups to enhance the functionalities of AGVS. Advanced AGVs use both sensors and AI to autonomously navigate in the facility without human guidance.
Table of Contents
Chapter 1: Strategic Imperatives
1.1 The Strategic Imperative 8™
1.2 Impact of the Top Three Strategic Imperatives of AGVs
1.3 About the Growth Pipeline Engine™
1.4 Growth Opportunities Fuel the Growth Pipeline Engine™
1.5 Research Process & Methodology
1.6 Key Findings
Chapter 2: Technology Landscape: Role of Sensors, AI, and Mobile Manipulators in AGVs
2.1 Automated Guided Vehicles Are Apt For Raw Material Handling For Work-in-progress Manufacturing Scenarios
2.2 AGV: Technology Landscape
2.3 Sensor Technology Trends Associated With AGVs - Key Sensor Technologies And Providers For AGVs
2.4 COVID-19 Pandemic Accelerated The Implementation Of Mobile Manipulator In E-commerce Order Fulfilment And Industrial Operation
2.5 Patenting Trends for AGV: The US Leads the World in Patent Filing
Chapter 3: Role of Computer Vision and Machine Learning in Automated Guided Vehicles
3.1 AI is Powering AGVs to Help Optimize Production
3.2 Machine Learning and Deep Learning Enhance AGV Capabilities
3.3 Applications of Computer/Machine Vision IN AGVs: Seamless Movement of Objects without Human Intervention
3.4 Applications of Computer/Machine Vision in AGVs for Barcode Reading, Inspection, Surveillance, and Security
Chapter 4: Companies To Action: Key AGV Developers
4.1 Key Participants
4.2 AI Companies Working on the Development of Robotic Vehicles Focusing in artificial intelligence aspects
Chapter 5: Use Cases
5.1 Use Case 1: Micron Technology, US
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: Leveraging Safety and Optimizing Costs in Production Facilities
Chapter 7: Key Contacts
Next Steps
- Your Next Steps
- Legal Disclaimer
Companies Mentioned (Partial List)
A selection of companies mentioned in this report includes, but is not limited to:
- BMW
- Micron Technology, US
- Unilever
- Universal Robots
