I would like to dedicate this episode to all the ROS Developers that are helping to build ROS a better framework. Not only the ones that are using ROS but the ones that are developing new packages, maintaining existing ones and adding new drivers and dependencies for new robots. If you are one of the ones that contributes to ROS, not only uses it, then this episode is dedicated to you.
But before going into that, let me remind you about our ROS online academy. Yes, at the Construct we have created an online academy named The Robot Ignite Academy which contains a ROS learning path for beginners. The path is composed by:
Of course all our courses are based on practice with simulated robots! (theory+practice)
Let me introduce you Sophia Kolak. Sophia is a software researcher at Carnegie Mellon university. In 2019 she presented a talk at the ROSCON 2019 entitled: It Takes a Village to Build a Robot: An Empirical Study of The ROS Ecosystem Today she is here to talk about her paper and why it matters for all ROS Developers.
I would like to dedicate this episode to all the ROS Developers that are using an embedded computer to control their ROS robot.
Today we are going to learn how we can optimize the Linux distribution for embedded computers and how we can use that with ROS.
But before going into that, let me remind you about our ROS online academy. Yes, at the Construct we have created an online academy named The Robot Ignite Academy which contains a ROS learning path for beginners. The path is composed by:
I would like to dedicate this episode to all the ROS Developers that are doing research on reinforcement learning applied to robotics. That is a difficult subject for which there is not much about it, specially with ROS. There are some works using other frameworks and simulators but not many that use ROS as their framework. So if you are in that field ROS + Reinforcement Learning + Robots, then this episode is dedicated to you.
Today we are going to learn how we can speed our development of such algorithms for ROS robots by using Gym-Ignition.
But before going into that, let me remind you about our ROS online academy. Yes, at the Construct we have created an online academy named The Robot Ignite Academy which contains a ROS learning path for beginners. The path is composed by:
Of course all our courses are based on practice with simulated robots! (theory+practice)
Now let me introduce you Diego Ferigo. Diego is a PhD fellow at Italian Institute of Technology, where he is doing research about using reinforcement learning for humanoid robot locomotion. Today he is here to talk about reinforcement learning with ROS, and about the framework he has developed for that, the Gym-Ignition.
Today we are going to learn about the current status of ROS2 Control, you know, the packages that allow us to control joints using ROS topics.
But before going into that, let me remind you about our ROS online academy. Yes, at the Construct we have created an online academy named The Robot Ignite Academy which contains a ROS learning path for beginners. The path is composed by:
Of course all our courses are based on practice with simulated robots! (theory+practice)
Now let me introduce you Bence Magyar. Bence and I we worked together at Pal Robotics. Now he works as Lead software engineer for FiveAI. But the main reason he is here with us today is because he is the main maintainer of the ROS control packages.
This episode is dedicated to all those pioneers that are building industrial applications with ROS2. That is a tough position to be because there is a lot of uncharted territory. It is very hard to get results. That is for the really brave ROS Developers. You are making ROS2 a reality in industry. Thank you for moving forward the frontiers of ROS2. This episode is dedicated to you.
Today we are going to talk with some guys from SWRI and ROS-Industrial consortium that have just done that: built hybrid applications with ROS1 and ROS2 on industrial robots.
But before going into that, let me remind you about our ROS online academy. Yes, at the Construct we have created an online academy named The Robot Ignite Academy which contains a ROS learning path for beginners. The path is composed by:
Of course all our courses are based on practice with simulated robots! (theory+practice)
Now let me introduce you Joseph Schornak and Jorge Nicho. They are research engineers at Southwest Research Institute in charge of software development for robotics systems in industrial environments. They are here today to talk about a hybrid ROS1 and ROS2 system for industrial robots that they have built.
This episode is dedicated to all those people that building humanoid robots with ROS and need extra care in their control algorithms (otherwise the robot falls down)
Today we have a super very special guest with who we are going to talk about how achieve real time control under ROS.
But before going into that, let me remind you about our ROS online academy. Yes, at the Construct we have created an online academy named The Robot Ignite Academy which contains a ROS learning path for beginners. The path is composed by:
Of course all our courses are based on practice with simulated robots! (theory+practice)
Now let me introduce you Luca Marchionni. What can I say about Luca? Luca and I we have worked together for 5 years at Pal Robotics designing navigation algorithms for the humanoid robots. Then Luca worked on problems of control of closed loop systems, whole body control, walking, motion planning and control for the human size humanoid robots built at Pal Robotics. For that he had to develop algorithms with real time control using ROS. Now Luca is the CTO of Pal Robotics and he is in charge of the technical vision of the company.
