MOV.AI and Lannar Electronics Meeting Global Demand for AMRs

May 06, 2022 by Stephanie Leonida

MOV.AI and Lannar Electronics collaborate to provide an integrated computing and software platform to speed up mobile robot development and deployment.

MOV.AI is a market-leading provider of development and deployment solutions for mobile robots. The company developed an operating system that offers a software framework for mobile robots so that they can be used safely alongside humans in any commercial or industrial environment and at any scale. On April 5, 2022, MOV.AI announced its entry into a collaboration with Lannar Electroncs Inc (Lannar Electronics) to provide autonomous mobile robot (AMR) manufacturers with an integrated computing and software platform for optimized performance and faster AMR development and deployment. Lannar Electronics is a Taiwan-based company that specializes in the provision of engineering and manufacturing services for advanced network appliances and rugged industrial computers.


MOV.AI and Lannar Electronics

MOV.AI and Lannar Electronics partnership. Image used courtesy of MOV.AI


The AMR Market

According to a summary from Fortune Business Insights, the global AMR market was valued at $1.67 billion in 2020 and is projected to grow from $1.97 billion in 2021 to $8.70 billion by 2028. This growth is expected to occur at a compound annual growth rate of 23.7%.

Since the start of the coronavirus pandemic, mobile robots have been in high demand to fill in gaps left by staff shortages and to remediate the negative impacts on global supply chains. The growth in the eCommerce industry, the need for new safety protocols, increasing dependency on automation solutions, and the creation of new robotic systems are all considered to be key drivers behind the growth of the global AMR market. In particular, logistics and warehousing/storage applications are among the primary targets of demand and application for AMRs.

Teaming up to Meet Market Demand

Together MOV.AI and Lannar will be delivering an integrated robotics solution combining MOV.AI’s robot operating system (ROS)-based Robotics Engine Platform with Lanner’s Edge artificial intelligence (AI) computing appliance. The LEC-2290E is a graphics processing unit (GPU) intelligent edge computing appliance with NVIDIA A2 GPU support. The device is designed for smart manufacturing applications, edge gateway, and intelligent video analytics. The LEC-2290E offers stability, longevity, as well as high availability.


Lannar edge computer

Lanner’s Edge artificial intelligence (AI) computing appliance, the LEC-2290E. Image used courtesy of Lannar Electronics


MOV.AI’s ROS-based Robotics Engine Platform provides robot manufacturers and automation integrators with software development tools, off-the-shelf autonomy algorithms, an open application programming interface (API) framework, deployment and maintenance tools, and easy upgrades to add new functionality or to keep up with changing standards.

In a news release from MOV.AI, The CTO of Lannar Electronics, Jeans Tseng, commented, “Lanner is pleased to partner with MOV.AI to offer the bundle solution that brings AMR to the industrial IoT edges.” Tseng added, “Our expertise in creating purpose-built Edge AI computers, combined with MOV.AI’s state-of-the-art Robotics Engine Platform, provides the industrial automation sector with a reliable AI-driven robotics solution that is both agile and intelligent.”


Advances in connectivity systems for industrial robots across multiple sectors introduce the increasing possibility of cyberattacks. A structural model such as the Purdue Model is necessary for securing industrial control systems (ICS). This model sets out the different levels of critical infrastructure (from the IT network down to the physical processes) used in production lines and how to secure them. Any disruption caused at some of these levels can cause hours or days of unwanted downtime.

A zero trust network architecture is a security model that is not based on the assumed trust of devices and users with a “network perimeter”. The zero trust model works by securing sensitive data behind least-privilege access controls, granular micro-segmentation, and multifactor authentication (MFA) that give no user or device implicit trust. The use of a zero trust framework can help organizations simply network infrastructures and improve cyber threat defense.

The International Organization for Standardization (ISO) is a global federation of national standards bodies (ISO member bodies) that sets international standards of all kinds. Although ISO 10218 and ISO 15066 standards provide guidance for robot safety they appear restricted to the safety-related consequences of security incidents. The development of AMRs is influencing changes in such standards to focus the attention of manufacturers toward enhanced cybersecurity.


Featured image used courtesy of Canva