We’re building the next generation of warehouse robotics. In the US today, retailers spend approximately $10B per year paying human laborers to pick up and move cardboard boxes in warehouses. Existing solutions for automating this are expensive and difficult to install, which is why manual operation is still so prevalent. Our solution is different. We make swarms of small mobile robots that install into existing warehouses to provide a low-cost and robust automation solution for case picking and mixed-SKU palletization. Our novel technology allows these robots to be installed and operate at significantly lower cost than existing solutions while being both flexible and robust.
Nathan is the co-founder and COO of AutoPallet Robotics. At 18, he graduated as the valedictorian of College of Alameda and then studied Engineering with Computing at Olin College where he met Eric. He has since built ML models for MBARI, consulted for the DIU (xView2) and WashU (drug discovery), and built core software for lab automation robotics at Trilobio.
Eric is the co-founder and CEO of AutoPallet Robotics. After graduating from Olin College in 2019, he led the Subject Tracking and Autonomy Infrastructure teams at Skydio, rapidly growing from individual contributor to lead a team of 6 engineers. Eric is a multidisciplinary robotics engineer with significant experience building modern robotics stacks, from hardware and electronics through perception and high-level software.
Nathan and Eric met at Olin College of Engineering 9 years ago, where they collaborated on over 15 projects.
CEO - Nathan brings four years of experience in machine learning. In his previous position, he worked on robot software and explored heuristic-based and RL-based methods for multi-robot scheduling.
CTO - Eric has extensive experience creating hardware, electronics, and software for modern robotics systems, including five years at Skydio, founding and growing the Autonomy Infrastructure team.
Case picking for order selecting, a critical task in the supply chain for grocery stores, retail, and restaurants, remains largely manual in U.S. warehouses. We estimate that over 30 billion cases are manually moved between pallets annually, resulting in labor costs exceeding $10 billion each year.
Current automation solutions are prohibitively expensive and fall into two main categories:
We've developed a way to retrofit existing warehouse infrastructure with swarms of affordable, agile robots to automate the order-selecting process. This approach eliminates the need to rebuild warehouses from scratch or invest in expensive large mobile robots. We are designing our system to:
We’re actively seeking partnerships and collaborations to propel our mission forward. If you or anyone in your network is interested in exploring opportunities or learning more, we’d love to connect! We’re especially interested in engaging with:
If this resonates with you or someone you know, please don’t hesitate to reach out! connect@autopallet.bot or send us an inquiry
Eric and Nathan met at Olin College, where they worked on 15 group projects together.