In this episode, Abate flew to Denver, Colorado, to get a behind-the-scenes look at the future of recycling with Joe Castagneri, the head of AI at Amp Robotics. With Materials Recovery Facilities (MRFs) processing a staggering 25 tons of trash per hour, robotic sorting is the clear long-term solution. Recycling is a for-profit industry. When the margins don't make sense, the items will not be recycled. This is why Amp's mission to use robotics and AI to bring down the cost of recycling and increase the number of items that can be sorted for recycling is so impactful. https://www.youtube.com/watch?v=QxiJLkFl7N0 Joe Castagneri Joe Castagneri graduated with his Master of Science in Applied Mathematics, with an undergrad degree in Physics. While still in university, he first joined the team at Amp Robotics in 2016 where he worked on Machine Learning models to identify recyclables in video streams of Trash in Materials Recovery Facilities (MRFs). Today, he is the Head of AI at Amp Robotics where he is changing the economics of recycling through automation.

Nico, Emil, and Moritz founded ReRun with the mission of making powerful visualization tools free and easily accessible for roboticists. Nico and Emil talk about how these powerful tools help debug the complex problem scopes faced by roboticists. Tune in for more. Nikolaus West Co-Founder and CEO Niko is a second-time founder and software engineer with a computer vision background from Stanford. He’s fanatic about bringing great computer vision and robotics products to the physical world. Emil Ernerfeldt Co-Founder and CTO Emil fell in love with coding over 20 years ago and hasn’t looked back since. He’s the creator of egui, an easy-to-use immediate mode GUI in Rust, that we’re using to build Rerun. He brings a strong perspective from the gaming industry, with a focus on great and blazing fast tools. Links ReRun Download mp3 Subscribe to Robohub using iTunes, RSS, or Spotify Support us on Patreon

Conventional sheet metal manufacturing is highly inefficient for the low-volume production seen in the space industry. At Machina Labs, they developed a novel method of forming sheet metal using two robotic arms to bend the metal into different geometries. This method cuts down the time to produce large sheet metal parts from several months down to a few hours. Ed Mehr, Co-Founder and CEO of Machina Labs, explains this revolutionary manufacturing process. Ed Mehr Ed Mehr is the co-founder and CEO of Machina Labs. He has an engineering background in smart manufacturing and artificial intelligence. In his previous position at Relativity Space, he led a team in charge of developing the world’s largest metal 3D printer. Relativity Space uses 3D printing to make rocket parts rapidly, and with the flexibility for multiple iterations. Ed previously was the CTO at Cloudwear (Now Averon), and has also worked at SpaceX, Google, and Microsoft. Links Machina Labs Download mp3 Subscribe to Robohub using iTunes, RSS, or Spotify Support us on Patreon

Joel Gibbard, co-founder of Open Bionics dives deep into their creative, imagination-capturing prosthetic limbs.

Dr. Tyler Reid, CTO of Xona Space Systems, discusses a new approach to global navigation satellite systems designed for self-driving cars.

Areeb, the co-founder of Glacier, gives some insight into the opaque recycling industry, and why it is unable to handle the volume of recyclable good Americans through out each year.

Deep Learning Indaba is an organization that empowers and builds communities around Artificial Intelligence and Machine Learning across Africa. Benjamin Rosman dives into how Deep Learning Indaba is impacting these communities.

Prof Brendan Englot, from Stevens Institute of Technology, discusses the challenges in perception and decision making for underwater robots - especially in the field.

Brady Watkins gives insights into how a large company like Softbank Robotics approaches the Robotics market

Dr. Sihao Sun on his research for controlling a quadcopter after one of its rotors faces a sudden failure. His research takes in real-world assumptions where the quadcopter may already be in a compromised, difficult to correct orientation.