Decision-Making Algorithms for Robotic Pallet Building
Jacopo Banfi
(Dexterity)
Event online by Webex
December 22nd, 2023
2.30 pm
Contatcs:
Francesco Amigoni
Research Line:
Artificial intelligence and robotics
(Dexterity)
Event online by Webex
December 22nd, 2023
2.30 pm
Contatcs:
Francesco Amigoni
Research Line:
Artificial intelligence and robotics
Sommario
On December 22nd, 2023 at 2.30 pm Jacopo Banfi, Robotics Engineer at Dexterity, will hold an online seminar on "Decision-Making Algorithms for Robotic Pallet Building".
Recent advances in artificial intelligence and robotics have started to rapidly revolutionize the supply chain, which plunged into a global crisis also caused by an unprecedented labor shortage following the outbreak of the Covid-19 pandemic. In this talk, I will describe the AI that powers Dexterity’s solution to the problem of robotic pallet building. In particular, I will introduce the 3-D Bin Packing problem as an idealized version of the robotic pallet building problem, and then present the unique challenges in solving it that are posed by operating in a real-world industrial setting. I will then talk about different AI techniques that can be used to make such a complex problem tractable, which ultimately allow Dexterity’s robots to build tall, dense, and stable mixed-case pallets with minimal human supervision.
Jacopo Banfi is a Robotics Engineer at Dexterity, Inc. (https://www.dexterity.ai/). Jacopo received his M.Sc. in Computer Science & Engineering and Ph.D. in Information Technology from the Polytechnic of Milan in 2014 and 2018, respectively. His Ph.D. thesis about multi-robot coordination under communication constraints was awarded the annual title of “best Italian Ph.D. thesis in Artificial Intelligence” from the Italian Association for Artificial Intelligence. Between 2018 and early 2022, he worked as a postdoctoral researcher at the University of Milan, Cornell University, and MIT on different robotics projects funded by the European Union, NASA, the U.S. Office of Naval Research, and the U.S. Army Research Laboratory.
In April 2022 he joined Dexterity, a robotics startup based in the Bay Area that builds innovative solutions to classical warehouse problems, where he currently works on autonomous truck loading and palletization problems.
Recent advances in artificial intelligence and robotics have started to rapidly revolutionize the supply chain, which plunged into a global crisis also caused by an unprecedented labor shortage following the outbreak of the Covid-19 pandemic. In this talk, I will describe the AI that powers Dexterity’s solution to the problem of robotic pallet building. In particular, I will introduce the 3-D Bin Packing problem as an idealized version of the robotic pallet building problem, and then present the unique challenges in solving it that are posed by operating in a real-world industrial setting. I will then talk about different AI techniques that can be used to make such a complex problem tractable, which ultimately allow Dexterity’s robots to build tall, dense, and stable mixed-case pallets with minimal human supervision.
Jacopo Banfi is a Robotics Engineer at Dexterity, Inc. (https://www.dexterity.ai/). Jacopo received his M.Sc. in Computer Science & Engineering and Ph.D. in Information Technology from the Polytechnic of Milan in 2014 and 2018, respectively. His Ph.D. thesis about multi-robot coordination under communication constraints was awarded the annual title of “best Italian Ph.D. thesis in Artificial Intelligence” from the Italian Association for Artificial Intelligence. Between 2018 and early 2022, he worked as a postdoctoral researcher at the University of Milan, Cornell University, and MIT on different robotics projects funded by the European Union, NASA, the U.S. Office of Naval Research, and the U.S. Army Research Laboratory.
In April 2022 he joined Dexterity, a robotics startup based in the Bay Area that builds innovative solutions to classical warehouse problems, where he currently works on autonomous truck loading and palletization problems.
Meeting link:
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