Core Viewpoint - The article discusses a new method of human-robot collaboration called COLA, which allows humanoid robots to interact and cooperate with humans using only proprioception, eliminating the need for external sensors [10][17][23]. Group 1: Introduction to COLA - The article introduces a scenario where a male student collaborates with a robot in various tasks, showcasing the robot's ability to assist without traditional controls [3][5]. - The interaction between the student and the robot is achieved through simple physical cues rather than remote controls or voice commands [8][10]. Group 2: Technical Aspects of COLA - COLA is a novel reinforcement learning method that enables humanoid robots to perform tasks by relying solely on proprioception, which includes internal sensory data like joint angles and force feedback [17][23]. - The method integrates two roles—leader and follower—into a single strategy, allowing the robot to switch roles seamlessly based on the human's actions [19][20]. Group 3: Training and Environment - The training environment for COLA is designed to be highly dynamic, simulating various real-world scenarios to prepare the robot for unexpected changes during tasks [21][22]. - The training process involves a feedback loop where the robot's actions influence the environment, and vice versa, creating a realistic interaction model [21][30]. Group 4: Performance and Validation - COLA has been tested in both simulated and real-world environments, demonstrating robust collaborative capabilities across various object types and movement patterns [35][36]. - Human participants rated COLA-controlled robots higher in terms of tracking and smoothness compared to other baseline methods, indicating superior performance [39][40]. Group 5: Research Team and Contributions - The research team behind COLA consists of members from the Beijing Academy of General Artificial Intelligence, with notable contributions from Yushi Du, Yixuan Li, and Baoxiong Jia [41][46]. - The team has published multiple papers in top conferences, showcasing their expertise in humanoid robotics and collaborative systems [45][47].