The ROS Developers Podcast

In this episode I talk to David Crawley founder of Ubiquity Robotics. He will explain about the idea of using built robots for building more complex robotics products and applications. He will also explain about: What their robotics platform provides off-the-shelf, in terms of hardware and software Their own ROS distribution for Raspberry Pi Their already

In this episode I talk to Florian Lier about what his team ToBI is doing to program Pepper the robot for the Robocup@Home competition. We will explain the whole architecture they are using to program Pepper with ROS for the competition including: In which computer to run which code ROS wrappers for NaoQi How to

In this episode I talk to one of the main developers of the Gazebo simulator: Louise Poubel. She tells us about the ins and outs of Gazebo, how do they organize at OSRF to develop the simulator, why to discard Gazebo 2 and how to install the newest versions. She will also clarify us what

In this episode, Jack Pien will talk about how to use accessible robots based on ROS and OpenCV to learn robotics. Those robots are called ROSbots and Jack is the creator of them. ROSbots come with ROS and OpenCV installed on a Raspberry Pi onboard the robot, ready for the user to create applications for

In this session of The ROS Developers Podcast, I chat with Cecilio Angulo, associate professor at Technical University of Catalonia and director of the Intelligent Data Science and Artificial Intelligence Research Center. We will talk about a project he started to bring Aibo robot back to life again by using ROS. He talks about how the whole thing started and why. Then he describes the different parts implemented in the Aibo

In this episode of The ROS Developers Podcast, I chat with Carlos Rosales, CTO of Beta Robots a company dedicated to apply ROS into real life industrial projects. He talks about the simulation model of the softhand, an open source hand with 5 fingers that is flexible and that absorbs collisions. He will also talk

In this episode, I interview Enrico Mingo Hoffman, postdoc researcher at the Humanoids & Human Centered Mechatronics Lab of the Italian Institute of Technology. He will talk about their open implementation of the Stack of Tasks for the whole body control of humanoid (and non-humanoid) robots. He will also explain how their development environment at the lab works, and will discuss some differences between ROS and YARP, another framework for robot programming developed at

In this episode, I interview Francisco Martin, associated professor at the University Juan Carlos I in Madrid, where he teaches robotics by using ROS. He is also a participant of the Robocup and the ROCKin competitions. He will explain how have they hacked Pepper the robot by means of using docker machines to cross-compile ROS

In this session of The ROS Developers Podcast, I chat with Sam Pfeiffer, who is a PhD student at University of Technology, Sydney where he leads the team of the University that goes to the Robocup with the Pepper robot. Among other things, he will explain us how he ROSified Pepper for that competition. He

In this episode, Ryan Gariepy CTO of Clearpath Robotics talks about how they use ROS for field service robots. He will explain how he uses vim for coding with ROS their field service robots. He will also express his point of view about the current status of ROS based on his large experience on using ROS for real life service robots. Finally, he

Summary In this episode, Luca Marchionni CTO of Pal Robotics talks about how they use ROS for their humanoid robots. He will specifically describe how they achieved to control with ROS a human size humanoid robot that walks and required real time control. He will also reveal how they attached the NASA Space Robotics Challenge in order to reach third

  Imagine how easy it would be to learn skating, if only it doesn’t hurt everytime you fall. Unfortunately, we, humans,  don’t have that option. Robots, however, can now “learn” their skills on a simulation platform without being afraid of crashing into a wall. Yes, “it learns“! This is possible with the reinforcement learning algorithms provided