Robohub.org
 

Bossa Nova raises $17.5 million for shelf-scanning mobile robots


by
19 November 2017



share this:

Bossa Nova Robotics, a Silicon Valley developer of autonomous service robots for the retail industry, announced the close of a $17.5 million Series B funding round led by Paxion Capital Partners and participation by Intel Capital, WRV Capital, Lucas Venture Group (LVG), and Cota Capital. This round brings Bossa Nova’s total funding to date to $41.7 million.

Bossa Nova helps large scale stores automate the collection and analysis of on-shelf inventory data by driving their sensor-laden mobile robots autonomously through aisles, navigating safely among customers and store associates. The robots capture images of store shelves and use AI to analyze the data and calculate the status of each product including location, price, and out-of-stocks which is then aggregated and delivered to management in the form of a restock action plan.

They recently began testing their robots and analytic services in 50 Walmart stores across the US. They first deployed their autonomous robots in retail stores in 2013 and have since registered more than 710 miles and 2,350 hours of autonomous inventory scanning, capturing more than 80 million product images.

“We have worked closely with Bossa Nova to help ensure this technology, which is designed to capture and share in-store data with our associates in near real time, works in our unique store environment,” said John Crecelius, vice president of central operations at Walmart. “This is meant to be a tool that helps our associates quickly identify where they can make the biggest difference for our customers.”

CMU grads launched Bossa Nova Robotics in Pittsburgh as a designer of robotic toys. In 2009 they launched two new products: Penbo, a fuzzy penguin-like robot that sang, danced, cuddled and communicated with her baby in their own Penbo language; and Prime-8, a gorilla-like loud fast-moving robot for boys. In 2011 and 2012 they changed direction: they sold off the toy business and focused on developing a mobile robot based on CMU’s ballbot technology. Later they converted to normal casters and mobility methods and spent their energies on developing camera, vision and AI analytics software to produce their latest round of shelf-scanning mobile robots.




Frank Tobe is the owner and publisher of The Robot Report, and is also a panel member for Robohub's Robotics by Invitation series.
Frank Tobe is the owner and publisher of The Robot Report, and is also a panel member for Robohub's Robotics by Invitation series.





Related posts :



Robot Talk Episode 135 – Robot anatomy and design, with Chapa Sirithunge

  28 Nov 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Chapa Sirithunge from University of Cambridge about what robots can teach us about human anatomy, and vice versa.

Learning robust controllers that work across many partially observable environments

  27 Nov 2025
Exploring designing controllers that perform reliably even when the environment may not be precisely known.

Human-robot interaction design retreat

  25 Nov 2025
Find out more about an event exploring design for human-robot interaction.

Robot Talk Episode 134 – Robotics as a hobby, with Kevin McAleer

  21 Nov 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Kevin McAleer from kevsrobots about how to get started building robots at home.

ACM SIGAI Autonomous Agents Award 2026 open for nominations

  19 Nov 2025
Nominations are solicited for the 2026 ACM SIGAI Autonomous Agents Research Award.

Robot Talk Episode 133 – Creating sociable robot collaborators, with Heather Knight

  14 Nov 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Heather Knight from Oregon State University about applying methods from the performing arts to robotics.

CoRL2025 – RobustDexGrasp: dexterous robot hand grasping of nearly any object

  11 Nov 2025
A new reinforcement learning framework enables dexterous robot hands to grasp diverse objects with human-like robustness and adaptability—using only a single camera.



 

Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


 












©2025.05 - Association for the Understanding of Artificial Intelligence