Presentation: From Robot Simulation to the Real-World
Share this on:
This presentation is now available to view on InfoQ.com
Watch video with transcriptAbstract
Simulation is one of the most powerful tools in the robot developer's tool belt. Besides allowing quicker, safer and cheaper iterations, it can be used to prototype before building, run continuous integration, train machine learning algorithms, etc. One popular open source robotics simulator is Gazebo, maintained by Open Robotics, the same foundation that maintains ROS, the Robot Operating System. Combined, ROS and Gazebo are used by an increasing number of developers around the world.
Gazebo's development started over 17 years ago, but its most current form started taking shape in 2012, when DARPA sponsored Open Robotics to run the Virtual Robotics Challenge, the first stage of its Robotics Challenge. A total of 26 teams competed in the virtual competition, controlling an Atlas robot from Boston Dynamics in a simulated disaster scenario. As a result of the virtual competition, the top 7 teams received funding to compete in the final competition with the same robot, but this time a physical one in a physical scenario.
Ever since, Gazebo has continued to be developed and improved to better support various types of robots, spanning ground, water and air, and is being increasingly used by the academia, industries and, sure enough, in other competitions. In this talk, Louise will give an overview of Gazebo's architecture and go over some examples of projects using Gazebo which Open Robotics has been involved with, describing how they bridged virtual robots to their physical counterparts.
2019 Tracks
-
AI Meets the Physical World
Where AI touches the physical world, think drones, ROS, NVidia, TPU and more.
-
Hands-on Codelabs & Speakers Office Hours
Codelabs are a self-guided tutorial of a product, API, or tool kit followed by an Office Hour period with the lab’s creator.
-
Papers in Production: Modern CS in the Real World
Groundbreaking papers make real-world impact.
-
Hands-on Codelabs & Speakers Office Hours
Codelabs are a self-guided tutorial of a product, API, or tool kit followed by an Office Hour period with the lab’s creator.
-
Solving Software Engineering Problems with Machine Learning
Interesting machine learning use cases changing how we develop software today, including planned topics touching on infrastructure optimization, developer experience, security, and more.
-
Predictive Architectures in the Real World
Case Study focused look at end to end predictive pipelines from places like Salesforce, Uber, Linkedin, & Netflix.
-
Predictive Data Pipelines & Architectures
Case Study focused look at end to end predictive pipelines from places like Salesforce, Uber, Linkedin, & Netflix
-
Sequential Data: Natural Language, Time Series, and Sound
Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.
-
ML in Action
Applied track demonstrating how to train, score, and handle common machine learning use cases, including heavy concentration in the space of security and fraud