用具身AI让无人机实时判断突发情况并自主决定安全降落。
Drones that Think on their Feet: Sudden Landing Decisions with Embodied AI
- 基于大视觉语言模型实现无人机环境感知与即时决策。
- 在虚幻引擎模拟城市环境中成功完成突发状况下的安全降落。
- 相比人工编码规则，具备更强的适应性和泛化能力，适合复杂场景应用。
自主无人机常需应对突发状况，如警报、故障或环境突变，要求即时且自适应的决策能力。传统方法依赖安全工程师手动编写大量恢复规则，但难以覆盖真实世界的多样化突发情况，很快变得不完整。近期，由大型视觉语言模型驱动的具身AI提供了常识推理能力，可实时评估上下文并生成恰当动作。我们在虚幻引擎构建的城市模拟基准中验证了这一能力，无人机能动态理解周围环境，并针对突发情况做出合适的机动决策以实现安全着陆。结果表明，具身AI使此前无法通过人工设计的自适应恢复与决策流程成为可能，显著提升了自主飞行系统在复杂环境中的鲁棒性与安全性。
原文摘要 · Abstract (English)
Autonomous drones must often respond to sudden events, such as alarms, faults, or unexpected changes in their environment, that require immediate and adaptive decision-making. Traditional approaches rely on safety engineers hand-coding large sets of recovery rules, but this strategy cannot anticipate the vast range of real-world contingencies and quickly becomes incomplete. Recent advances in embodied AI, powered by large visual language models, provide commonsense reasoning to assess context and generate appropriate actions in real time. We demonstrate this capability in a simulated urban benchmark in the Unreal Engine, where drones dynamically interpret their surroundings and decide on sudden maneuvers for safe landings. Our results show that embodied AI makes possible a new class of adaptive recovery and decision-making pipelines that were previously infeasible to design by hand, advancing resilience and safety in autonomous aerial systems.
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