How Robot Care System uses cloud computing to enhance its LEA smart walker
A walker is a simple tool, designed to provide support and balance for people with ambulatory and balance difficulties. But what if a walker could talk to you, detect falls, and intelligently avoid hazardous obstacles — all while powered by cloud computing? That’s the idea behind Robot Care System’s Lean Empowering Assistant, or LEA.
LEA is a smart walker designed to improve mobility and independence for individuals with diseases like Parkinson’s or who are at risk of falling. Robot Care Systems is now making the second generation of LEA more efficient, smarter, and more powerful, thanks to the tools provided by Amazon Web Services (AWS).
The first generation of LEA featured over 70 sensors and could do things like automatically adjust for balance, call family and friends, encourage exercise, and set medication reminders. As advanced as this device was, it was limited in its computing power. As a result, utilizing machine learning models, predicting maintenance needs, and processing voice commands were far beyond LEA’s onboard computing system’s capacity.
However, these capabilities were high on customers’ wish lists of features. By adopting AWS cloud services and building robotics applications with AWS RoboMaker, Robot Care Systems can now deliver these and other advanced features to customers.
LEA gets smarter with ROS, RoboMaker, and the cloud
AWS RoboMaker works by providing cloud extensions for Robot Operating System (ROS) and allows users to develop, test, simulate, and deploy advanced robotics applications. With RoboMaker, the second-generation LEA will be more intuitive, safer, and more efficient for customers to use.
Adopting cloud computing will allow developers to manage data from all LEA robots for machine-learning model training. This information processing will help increase the scale and speed at which their robots can learn from each other and function better for customers.
In addition, RoboMaker allows Robot Care Systems to create managed robotics simulations, in which developers can test and evaluate how their robots will behave in certain situations. These simulations are conducted virtually via the Web console, thus saving the time, cost, and operational burden of having to physically deploy, test, and capture data from additional robots.
Migrating to cloud computing will help Robot Care Systems grow its current fleet from 100 domestic robots to more than 10,000 across the globe. Also, maintaining robots becomes easier in the cloud. The current state of maintenance operations requires on-site visits by human technicians, but with updated cloud-supported fleet management, the group can receive diagnostic alerts and push out bug fixes and software updates remotely.
Behind the scenes, RoboMaker alone is not powering LEA’s increased computing power. Switching to the AWS cloud opens up the possibilities to incorporate hundreds of other features and services into a robotics application. The next generation of LEA uses other AWS services such as SageMaker, Lex, Polly, and Rekognition to add and test even more features.
Amazon Lex and Polly will be used to test and deploy a natural language processing (NLP) voice interface for LEA, giving the device a new way to interact with users. Meanwhile, SageMaker, a machine learning program, will help Lea better identify risk factors for users by improving movement and behavior detection. AWS RoboMaker opens the door for innovation, with access and compatibility to a variety of innovative AWS services.
Robot Care System is one example of how a company has been able to evolve and enhance its product via cloud computing and AWS RoboMaker, with other companies following suit. Companies are deploying robotic arms, drones, and ground robots in innovative ways every day. As the diversity and sophistication of robot applications expand, these breakthroughs demand a high level of intelligence and autonomy. AWS provides the infrastructure and tools to support such innovation.
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