[Beijing/New York] – In a significant stride towards realizing the long-awaited dream of household robots, a team led by renowned AI researcher Lee Fei-Fei has introduced the BEHAVIOR Robot Suite (BRS), a comprehensive framework designed to tackle the challenges of whole-body manipulation in household environments. What’s particularly remarkable is the cost-effectiveness of the BRS, with its core components costing less than $500.
While robots are increasingly demonstrating impressive feats like running and performing backflips, their practical application in everyday household chores has remained elusive. The BRS aims to bridge this gap by addressing the complexities of enabling robots to perform a wide range of domestic tasks.
The BRS is built upon three key capabilities deemed essential for successful completion of household activities:
- Dual-Arm Coordination: The ability for the robot to seamlessly coordinate the movements of its two robotic arms.
- Stable Navigation: Ensuring the robot can navigate complex home environments with precision and stability.
- Extensive End-Effector Manipulation Range: Providing the robotic arms with a wide range of motion and reach to interact with objects in various locations and orientations.
The team identified the critical importance of end-effector control, an often-overlooked aspect. In a typical home, objects are located at varying heights and positions, requiring the robot to adjust its reach accordingly.
To achieve these capabilities, the team opted for a dual-arm mobile robot platform with a flexible torso. They selected the Galaxea R1 robot, manufactured by Chinese company StarField Robotics, which features two 6-DOF (degrees of freedom) arms, each equipped with a parallel jaw gripper, a 4-DOF torso, and an omnidirectional mobile base.
Imagine a robot capable of:
- Opening a door to take out the trash in the morning.
- Organizing groceries after a shopping trip.
- Tidying up the living room and loading dirty dishes into the dishwasher.
- Even scrubbing the toilet.
The BRS framework aims to make such scenarios a reality. Moreover, the research team has observed that the robot can even self-correct when encountering obstacles during task execution.
The team leverages a low-cost teleoperation interface called JoyLo and a learning algorithm called WB-VIMA to achieve efficient data collection and coordinated whole-body movements.
The BRS represents a significant step forward in embodied AI research, bringing us closer to a future where robots can assist with everyday household tasks. The affordability of the system, combined with its focus on essential manipulation skills, makes it a promising platform for further research and development in this field.
References:
- QubitAI. (2024). 李飞飞团队具身智能新作：500美元，一切家务机器人帮你干 [Lee Fei-Fei’s Team’s New Embodied Intelligence Work: $500, All Household Chores Done by Robots]. Retrieved from [Insert original article link here if available, otherwise remove this line]
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