Intelligent Robotics with AI
Intelligent Robotics uses AI to boost collaboration between people and devices. AI helps robots to adapt to dynamic situations and communicate naturally with people.Get started on ROS code
Robotics can help automate tasks that are repetitive, dangerous, or vulnerable to human error. However, automation without intelligence creates a system that cannot respond to variables, new environments, or dynamic requirements.
Combining AI with robotics creates smarter autonomous systems. With machine learning, image recognition, cognitive services, and more—robots can learn and respond to requirements, beyond simple commands.
AI provides a platform to develop intelligent bots. By adding cognitive services to the bot, we can make our bot smart—with capabilities like language understanding, image recognition, text recognition, translation, and more.
Code the future of Intelligent Robotics
Infusing advanced robotics with AI enables the next generation of robotics to be collaborative, assistive, and cognitive.
Technical details of Intelligent Robotics
Building an Intelligent Robot
In this lab, you will learn about the heart of robotics programming using the Robot Operating system (ROS) with Python and how to use Gazebo, the robot simulator. You will also learn how to deploy your code to a real industrial robot. This lab will give you the confidence to start your journey with intelligent collaborative robotics.
This lab uses a collaborative robot based on Sawyer from Rethink Robotics named Paul-E. You do not need an actual robot; this lab is a simulation.
Paul-E is a 7 degree of motion, integrated collaborative robot (aka cobot) designed with embedded vision, smart swappable grippers, and high-resolution force control. The robot purpose is to automate specific industrial repetitive tasks, it comes with an arm that has a gripper which can be easily replaced
For this lab, we use 3 tools: ROS, Gazebo, and RViz.
ROS is a robotics middleware licensed under an open source. ROS provides libraries, hardware abstraction, device drivers, visualizers, message-passing, package management, and other tools to help software developers create robot applications.
Gazebo allows to build 3D scenarios on your computer with robots, using obstacles and other objects. This allows to test robots in complex or dangerous scenarios without any harm to the real robot.
Rviz is an Open Source 3D visualizer that uses sensors data and custom visualization markers to develop robot capabilities in a virtual environment.
Making your robot intelligent
Microsoft Bot Framework and Cognitive Services provide a platform to develop intelligent bots. By adding cognitive services to the bot, we are able to make our bot smart and have capabilities like language understanding, image recognition, text recognition, translation, and more.
In this lab you will create a simple bot, then enable this bot to communicate with a physical robot, using natural language and computer vision for image recognition.
Intelligent robotics architecture
In the diagram, the main controller includes REST interface, task planner, vision system, motion planner, and Robot Operation System (ROS). The Sawyer Robot Controller uses ROS and an embedded controller. These 3 tiers work together to power intelligent robotics.
AirSim - Drones
AirSim is a simulation tool that creates a 3D version of a real environment. A simulated drone “flies” to capture images, building a custom vision model. AI uses the vision model to identify objects or people.
Explore the concepts of machine teaching, allowing developers or subject matter experts with little AI expertise to provide abstract concepts to an intelligent system.
Machine Reading Comprehension (MRC) answers questions about written text. Using a neural network, MRC mimics the process of human readers. Ask a question and MRC reads a document until an answer is formed.
Responsible Conversational AI
Conversational AI is a new way for companies to interact with their customers across any channel, like digital assistants, chat or social media. To be effective, conversational bots need to be developed in a way that earns people’s trust.
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