How can code-driven robots better interact with humans? Recently, Brown University's Human-Robot Robotics Lab tested a new AI-enabled system that aims to make robots understand human commands in everyday language and perform tasks accurately.

If the research achieves results, it will be applied to many mobile robots in the city in the future, including drones, self-driving cars, unmanned transport vehicles, etc., you only need to use the usual way of communicating with people to interact with the robot, he can accurately understand your instructions, making the application of mobile robots in complex environments possible.

To test the system, the researchers ran simulations using OpenStreetMap in 21 cities and showed that the system performed the task accurately 80 percent of the time, a much higher accuracy rate than other similar systems, which typically only achieve about 20 percent accuracy and cannot handle complex instructions and tasks.

At the same time, the team also conducted indoor testing on the Brown University campus with Boston Dynamics' spot robot, which is considered one of the world's leading general-purpose quadruped robots, and the success of the verification on spot will facilitate the applicability of the system to robots from other manufacturers.

A simulation based on OpenStreetMaps will be posted online in November, allowing users to test the system for themselves. Users can enter natural language commands on a web page to guide a simulated drone on a navigation task to help researchers fine-tune the software.

This means that an "AI+ robot" project jointly trained by the public is coming to us.