智元办机器人挑战赛：清华&上海AILab夺冠，华南理工“单人成团”拿亚军

Core Insights - The AGIBOT World Challenge, organized by Zhiyuan Robotics and OpenDriveLab, concluded successfully in Hangzhou during IROS, showcasing intense competition among top global teams in various physical tasks [2][4][48] - The AIR-DREAM team from Tsinghua University and Shanghai AI Lab won the championship, while South China University of Technology and the University of Hong Kong secured the second and third places respectively [4][10][50] Competition Overview - The competition featured 11 elite teams from around the world, competing in six real-world physical tasks such as object manipulation, dynamic sorting, and kitchen operations [4][6][19] - The event aimed to test the operational precision and generalization capabilities of embodied intelligent systems [6][19] Task Details - Each team performed 10 attempts per task, with scores averaged for the final results, using the UniVLA baseline model [20] - The six tasks included: - Pack groceries: Teams had 90 seconds to grab three snacks and place them in a bag, with a maximum score of 6 points [22][24] - Pack items from conveyor: In 90 seconds, teams needed to identify and grab items from a moving conveyor, also scoring up to 6 points [26][29] - Fold short sleeves: Teams had 150 seconds to fold clothing, with a maximum score of 4 points [30][32] - Microwave the food: This task involved a series of steps to operate a microwave within 150 seconds, scoring up to 6 points [35][37] - Restock the hanging area: Teams had 60 seconds to place items on shelves, scoring up to 2 points [39][41] - Pour water: In 60 seconds, teams had to pour a specified amount of water, with a maximum score of 4 points [43][45] Technical Insights - The AIR-DREAM team introduced the X-VLA model, a scalable and simplified visual-language-action model that addresses challenges in heterogeneous robot data [11][13] - The second-place team shared strategies for achieving high success rates with limited computational resources, focusing on quick fine-tuning of pre-trained models [15] - The third-place team utilized a pre-trained model and a simulation platform for data generation and parallel reinforcement learning, achieving efficient technical solutions in a short timeframe [17] Event Highlights - The AGIBOT World Challenge featured a total prize pool of $560,000, with the manipulation track offering $60,000, and the champion team receiving $10,000 [48][51] - The event also highlighted the launch of the new "archery" robot, the Spirit G2, which was showcased for the first time at IROS [53]