Robotics

Six robots complete 1,730 tasks in Shanghai store trial

The Robot Report: Six AGIBOT G2 Robots Complete 1,730 Tasks in 24-Hour Shanghai Convenience Store Trial

Four of the six robots pass a performance assessment as the trial puts customer service, retail operations and embodied AI capabilities to the test in a working store. Six AGIBOT G2 wheeled humanoid robots completed a 24-hour trial at an operating convenience store in Shanghai’s Xuhui District, performing a combined 1,730 tasks ranging from customer assistance and coffee preparation to shelf restocking and cleaning. The trial ran from 10 a.m. on November 2 to 10 a.m. on November 3 an

Get smart on it

Six wheeled humanoid robots completed 1,730 tasks over a 24-hour period in an operating convenience store, performing duties ranging from customer service and food preparation to shelf restocking and cleaning. The trial tested whether robots could handle real-world retail conditions with constantly changing circumstances, such as variations in product placement and customer movement, rather than operating only in controlled environments. Four of the six robots passed a final performance assessment that evaluated their ability to complete tasks, respond to unexpected situations, and adapt to different operating periods throughout the day. The trial demonstrated how the robots' AI framework could coordinate multiple units, learn from execution feedback, and apply previous experience to improve performance on similar tasks.

Read next
The biggest AI stories, once a day

One short email a day with the stories that matter. Free. Unsubscribe with one click.

Relevant courses

Want to go deeper than the news? Explore live, cohort-based AI courses taught by practitioners.

Browse AI courses on Maven
Related news
RoboticsOpen story →

Google DeepMind releases new advanced robotics AI model and next-generation gene prediction model

Alphabet Inc.’s artificial intelligence research lab, Google DeepMind, Tuesday debuted the next generation of Gemini Robotics, the company’s most capable vision-language-action model to date for creating an “AI brain” for robotics. Separately, DeepMind announced AlphaGenome 2 today, a next-generation AI model that can predict how DNA sequences and their variations affect human cell types, creating […] The post Google DeepMind releases new advanced robotics AI model and next-generation gene

Also reported by MarkTechPost and The Decoder

RoboticsOpen story →

Gemini Robotics 2.5 accelerates real-world general dexterity

Our most capable vision-language-action model enhances robot dexterity, reliability, and safety

Also reported by Ars Technica

RoboticsOpen story →

How Rhoda AI is using video data to create generalized AI models for robots

Rhoda pretrains its models on internet-scale video to build a strong prior on motion, physics, and physical interaction. | Source: Rhoda AI Earlier this year, Rhoda AI emerged from 18 months of stealth with $450 million in Series A funding. The company is working with customers in automotive, manufacturing, logistics, and e-commerce to deploy its direct video action, or DVA, model for robotics. “We’re focused on deploying in the real world, and that means you have to deal with the messiness of t

RoboticsOpen story →

Ring, known for its doorbell cameras, launches a home security drone and an enterprise security robot

Amazon-owned Ring is pushing into robotics with the launch of a home security drone and a rolling robot designed to patrol and protect businesses.

Also reported by Ars Technica

RoboticsOpen story →

Can AI agents program industrial robots without training data? Berkeley says yes

The new RoboSimStudio is an open-source project that enables agentic AI coding of robotic simulation environments. | Credit: UC Berkeley UC Berkeley and NVIDIA have released open-source tools for a new approach: enabling teams of AI coding agents to write, simulate, and refine readable robot programs. Since the early days of industrial robots, programming, tuning, and troubleshooting robotic workcells has taken weeks to months. New research coming out of UC Berkeley has demonstrated that new age

RoboticsOpen story →

Memories.ai builds standardized egocentric video pipeline

Memories.ai models label every clip: Memories-H0 for hand pose, EgoAction for action segments. | Credit: Memories.ai Memories.ai is building a data pipeline for robotics companies that combines standardized video collection with AI-powered annotation to turn everyday egocentric footage into training data for robots. The San Francisco-based company is developing software and AI to help robots understand the physical world. It builds video-understanding models and data infrastructure, and it colle