Google DeepMind 新 AI 模型可控制机器人全身

Google DeepMind 表示，其最新版 Gemini Robotics AI 模型能够“控制完整的人形机器人”。此前的模型主要专注于控制人形机器人的上半身，而据该公司周四发布的公告，Gemini Robotics 2 现已支持从足部到指尖的“全身动作”。

该新模型将让人形机器人能够执行更广泛的动作，包括行走、下蹲、伸展以及操作物体。Google 分享的视频展示了 Apptronik 的 Apollo 2 机器人如何弯腰拾起一个浇水壶，以及如何在货架上寻找并取下特定物品。

尽管 Google DeepMind 指出，其机器人“在运动速度方面仍有待提升”，但该公司补充称，这次更新“是迈向完成更复杂现实世界任务所需技能的重要一步”，而这类任务需要全身协调能力。

此外，Gemini Robotics 2 还支持更强的灵巧操作能力，现在可控制更复杂的五指手。这使机器人能够完成密封 Ziploc 密封袋、扎紧垃圾袋或拧下灯泡等任务。

Google DeepMind 也在更新 Gemini Robotics ER（具身推理），这是一种视觉语言模型，可帮助机器人分析周围环境、处理指令并执行多步骤任务。Gemini Robotics ER 2 在更长时间内完成任务的能力更强，并且“现在能够理解任务何时开始和结束”。

Google DeepMind 表示，此次更新还使多台不同类型的机器人能够协作完成任务。其中一段视频展示了 Apollo 2 如何在清理车库时，指示 Google 的双臂机器人将工具放入收纳箱中。

该公司称，Gemini Robotics ER 2 是其“迄今为止最安全的机器人模型”，因为它能“更好地检测附近是否有人、触发安全工具调用，并在有人靠得过近时让机器人安全停止”。

与此同时，Google DeepMind 还改进了 Gemini Robotics On-Device Model。该模型无需互联网连接即可在机器人本地运行。该模型现在能够更快地适配新的机器人本体，包括那些“形态、传感器和自由度存在显著差异”的机器人。

Google DeepMind says the latest version of its Gemini Robotics AI model can “control entire humanoid robots.” While the previous model focused on controlling a humanoid robot’s upper body, Gemini Robotics 2 now supports “whole-body motions” ranging from its feet to fingertips, according to an announcement on Thursday.

The new model will allow humanoid robots to perform a wider range of actions, as it allows them to walk, crouch, stretch, and manipulate objects. Videos shared by Google show how Apptronik’s Apollo 2 robot can bend over to pick up a watering can, as well as find and take specific items off a shelf.

Though Google DeepMind notes that its robots “have more to advance in movement speed,” it adds that this update “is an important step towards the skills needed to complete more complex, real-world tasks that require whole-body coordination.”

Additionally, Gemini Robotics 2 supports better dexterity, as it can now control more complex, five-fingered hands. That enables robots to perform tasks like sealing a Ziploc, tying a trash bag, or unscrewing a lightbulb.

Google DeepMind is updating Gemini Robotics ER (embodied reasoning) as well, a vision-language model that helps robots to analyze their surroundings, process instructions, and perform multi-step tasks. Gemini Robotics ER 2 is better at completing tasks over an extended period of time and “now understands when tasks begin and end.”

Google DeepMind says this update also allows multiple robots of different types to work together and complete tasks, with one video showing how Apollo 2 instructs Google’s dual-arm robot to put tools inside a bin while cleaning the garage.

The company notes Gemini Robotics ER 2 is its “safest robotics model to date,” as it can “better detect when humans are nearby, trigger safety tool calls and bring the robot to a safe stop if someone approaches too closely.”

Meanwhile, Google DeepMind has brought improvements to its Gemini Robotics On-Device Model, which can run locally on a robot without an internet connection. This model can now adapt to new embodiments faster, including those with “drastically different shapes, sensors and degrees of freedom.”