Core Viewpoint - Google DeepMind has launched the Gemini Robotics 1.5 series, marking a significant advancement in robotics with the introduction of embodied reasoning capabilities, enabling robots to think before acting and perform complex tasks [3][5][10]. Group 1: Model Composition - The Gemini Robotics 1.5 series consists of two models: GR 1.5 for action execution and GR-ER 1.5 for enhanced reasoning capabilities [6][4]. - GR 1.5 is designed for executing multimodal tasks, while GR-ER 1.5 focuses on planning and understanding [6][23]. Group 2: Task Execution and Adaptability - The combination of GR 1.5 and GR-ER 1.5 allows robots to perform multi-step tasks, such as sorting clothes or packing luggage based on weather conditions [7][8][20]. - The models enable zero-shot cross-platform capability, allowing skills learned on one robot to be transferred to another without additional training [9][19]. Group 3: Reasoning and Planning - GR-ER 1.5 generates an internal dialogue to break down complex tasks into smaller steps before execution, enhancing robustness and interpretability [25][50]. - The models can self-correct during task execution, improving efficiency and safety in human environments [31][32]. Group 4: Motion Transfer Mechanism - The innovative Motion Transfer mechanism allows different robot platforms to share skills by mapping their motion trajectories to a unified action semantic space [46][52]. - This mechanism enhances task generalization and cross-robot migration capabilities, allowing robots to adapt to new environments effectively [47][53]. Group 5: Performance and Safety - In benchmark tests, GR 1.5 outperformed previous models in instruction generalization, action generalization, and task completion rates, achieving nearly 80% in long-sequence tasks [58][59]. - The models maintain high safety standards, demonstrating superior risk recognition and intervention capabilities, ensuring safe operation in human environments [61][62].