用自然语言动态调整机器人路径，让非专业用户也能灵活控制。
OVITA: Open-Vocabulary Interpretable Trajectory Adaptations
- 通过大模型生成代码实现路径点的灵活修改
- 支持多类机器人在真实环境中的轨迹适配
- 无需专业知识，用户可直观理解并操作
在非结构化环境中，为非专业用户提供灵活的机器人轨迹调整能力至关重要。自然语言使用户能以交互方式表达调整需求。我们提出OVITA——一种可解释、开放词汇、基于语言驱动的轨迹自适应框架，可根据人类指令在动态和新情境下调整机器人轨迹。该框架利用多个预训练大语言模型（LLMs），将用户指令融入运动规划器生成或示范学习的轨迹中。通过由LLM生成的代码作为调整策略，用户可对单个路径点进行修改，实现灵活控制；另一大模型作为代码解释器，消除专家门槛，实现直观交互。在包含时空变化的多样化任务中，通过大量仿真与真实环境验证，展示出在KUKA IIWA机械臂、Clearpath Jackal地面机器人及CrazyFlie无人机等异构平台上的有效性与实用性。
原文摘要 · Abstract (English)
Adapting trajectories to dynamic situations and user preferences is crucial for robot operation in unstructured environments with non-expert users. Natural language enables users to express these adjustments in an interactive manner. We introduce OVITA, an interpretable, open-vocabulary, language-driven framework designed for adapting robot trajectories in dynamic and novel situations based on human instructions. OVITA leverages multiple pre-trained Large Language Models (LLMs) to integrate user commands into trajectories generated by motion planners or those learned through demonstrations. OVITA employs code as an adaptation policy generated by an LLM, enabling users to adjust individual waypoints, thus providing flexible control. Another LLM, which acts as a code explainer, removes the need for expert users, enabling intuitive interactions. The efficacy and significance of the proposed OVITA framework is demonstrated through extensive simulations and real-world environments with diverse tasks involving spatiotemporal variations on heterogeneous robotic platforms such as a KUKA IIWA robot manipulator, Clearpath Jackal ground robot, and CrazyFlie drone.
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