One business who realized that using artificial intelligence (AI) and machine learning is a business need, no longer a competitive advantage is PepsiCo. The food-and-beverage company behind brands such as Pepsi, Gatorade, Tropicana, Lipton, Frito-Lay, and Quaker sells products in more than 200 countries and brought in $64.7 billion in annual revenue last year. From robots to machine learning, PepsiCo uses AI and machine learning throughout the organization in many ways. There's a six-wheeled mobile vending machine robot tooling around the University of the Pacific chockful of PepsiCo snacks and beverages from Hello Goodness--a healthier line-up that includes SunChips, Baked Lay's and bubly sparkling water. Named Snackbot, these self-driving robots are a partnership between Robby Technologies and PepsiCo.

The mobile vending machine that PepsiCo recently launched at University of the Pacific has caused excitement among college students craving for a quick refreshment, but the U.S. food giant suggested that this is only the tip of the iceberg of when it comes to providing food service using artificial intelligence. The self-driving robots, named as Snackbot, were developed through a partnership between PepsiCo and the Bay Area-based Robby Technologies. At the moment, they deliver snacks and beverages from PepsiCo's better-for-you portfolio Hello Goodness, which includes Smartfood Delight, Baked Lay's, SunChips, Pure Leaf Iced Tea, bubly, LIFEWTR and Starbucks Cold Brew. The Hello Goodness range was launched in 2015, and it has been boosting PepsiCo's e-commerce and vending businesses. The company previously conducted a Hello Goodness store test on Amazon back in 2017, and it showed its healthy snacking portfolio performed nearly 45% better than the sales from other similar campaigns and return on investment for advertising.

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. A new version of the four-legged "Jueying" robot was released on Dec. 4. The new "Jueying" robot, a small-sized quadruped robot that can handle 20 kg objects, is capable of running and climbing stairs.

Today, PepsiCo announced that it will be rolling out a fleet of snack-carrying robots on the University of the Pacific's campus in California. The robots -- or "snackbots" -- carry snacks and beverages from the company's Hello Goodness portfolio, which includes choices like Smartfood Delight popcorn, Baked Lays, Pure Leaf Tea, and Starbucks Cold Brew drinks. Students can place their orders on the iOS app and have them delivered to select locations around the 175-acre campus between 9AM and 5PM. The snackbots are nearly identical to the other delivery machines we've seen before. They can travel 20 miles on a single charge, and they have headlights and a camera.

If walking to a regular vending machine seems too inconvenient, what if the vending machine came to you? PepsiCo is doing just that at the University of Pacific campus in Stockton, California with robots called "snackbots." Using a smartphone app, students can order quasi-healthy snacks like Baked Lays, Sunchips or a Starbucks Cold Brew (from PepsiCo's "Hello Goodness" vending platform), and have it delivered between 9 AM and 5 PM to one of 50 locations around the 175 acre campus. The autonomous snackbots, built by Y-Combinator startup Robby Technologies, can travel 20 miles on a charge, and are equipped with a camera, headlights and all-wheel drive to handle rough or wet terrain. Once it arrives, you simply release the lid, grab your snacks and close it to complete the sale. The app presumably takes care of the security and dispensing end of things.

Snackbot is the first snack-delivering robot in the U.S. to be backed by a major food and beverage company. The snackbot is an outdoor, self-driving robot. Students at University of the Pacific are about to have a futuristic dream come true: a robot that delivers you snacks. PepsiCo's Hello Goodness brand, which was created in 2015 to provide healthier snacks and beverages to consumers on the go, partnered with the San Francisco Bay Area-based Robby Technologies to bring this self-driving snack robot -- or "snackbot" -- to life. From 9 a.m. to 5 p.m., students at the private university in Stockton, California, can order food and drinks to one of more than 50 locations across campus through the snackbot app.

Compressed air flows beneath silicone skin, triggering actuators that raise her arms and lift the corners of her mouth into a demure smile. She seems to compose herself, her eyes panning the room where she stands fixed to a platform, tubes and wires running down through her ankles. She blinks, then turns her face toward me. I can't help but meet her--its--mechanical gaze. "Are you surprised that I'm a robot?" she asks.

For five months in 2011, a robot wheeled around an office building at Carnegie Mellon University delivering bananas, cookies, and other afternoon snacks to workers. With wide-set eyes and a pink mouth, Snackbot had a friendly look, but it was prone to mistakes. Long delays in conversations with workers were common. Sometimes the system running Snackbot froze. Still, the workers became comfortable with Snackbot.

Robot designers commonly emphasize humanlikeness as an important design feature to make robots social or user-friendly. To understand how users make sense of the design characteristics of robots, we asked 6 participants to classify and interpret the appearance of existing robots in relation to their function and potential usefulness. All the robots had humanlike aspects in their design, and participants most commonly remarked on these humanlike features of the robots. However, the commonsense logic of the “Uncanny Valley” (UV) in HRI design, which suggests that robots should be similar to humans to some degree without being too humanlike, was not supported by participant comments, which did not correlate humanlikeness to user-friendliness in line with the UV hypothesis. Rather, participants related the design features of robots to their everyday contexts, and focused their commentary on context-dependent design implications. As a result, we suggest our understanding of the design characteristics of robots should include the perspectives of users from the earliest stages of design so we can understand their contextual interpretations of different design characteristics. Open and modularized technical platforms could support the inclusion of users in the creation of future social robots.

While delivering snacks, Snackbot’s need to actively engage in conversation with the customers and other individuals, provides an approach for verbal interaction. This paper addresses the verbal human-robot interaction between humans and robots using a speech recognizer named Sphinx-4. Sphinx-4, written entirely in Java is capable of recognizing predetermined words and sentences. Thereby, allowing robots to actively engage in conversations using spoken language.