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世界人形机器人运动会|对话单机舞蹈冠军北京通用人工智能研究院:备赛经验值回“票价”
Bei Jing Shang Bao· 2025-08-17 09:08
Core Viewpoint - The BIGAI-Unitree team, a collaboration between the Beijing General Artificial Intelligence Research Institute and Yushutech, won the championship in the solo dance category at the World Humanoid Robot Games, showcasing their advanced robotics technology and integration of algorithms and hardware [3][16]. Group 1: Competition and Performance - The BIGAI-Unitree team utilized Yushutech's G1 humanoid robot hardware combined with their own algorithms to compete in various events, including solo dance and scene skill competitions [7]. - The dance performance included elements of both traditional Chinese and Western dance styles, demonstrating the robot's versatility [3]. - The team aimed to place in the top three for the dance event and had lower expectations for the scene competition due to the use of bipedal robots versus wheeled robots [15]. Group 2: Collaboration and Research - The collaboration between the research institute and Yushutech focuses on a division of labor where the institute develops algorithms (the "brain") while Yushutech concentrates on hardware [4][11]. - The competition provided valuable insights into real-world challenges that differ from laboratory conditions, particularly regarding wireless communication issues [12][13]. - The experience gained from the competition will inform future research directions, emphasizing the need for models that can quickly adapt to new environments without extensive retraining [14]. Group 3: Technical Challenges and Insights - The competition highlighted technical challenges such as insufficient wireless bandwidth and interference, which affected performance [12]. - The research institute views these challenges as opportunities to improve their models and algorithms, focusing on balancing model size, capability, and performance [13]. - The success in the dance competition reflects the effectiveness of their "Intelligent Brain" technology, while the scene competition results revealed areas for improvement [16].