飞行、驾驶、重构：面向现场作业的模块化可重构空地平台

中文摘要 AI 辅助

异构机器人团队将互补能力分配给专门的智能体，但其物理角色和能力通常在任务过程中保持不变。我们提出了HARP，一个异构空中机器人模块平台，其中可独立部署的空中机器人通过物理重构来组合其能力，以支持现场作业。HARP由配备传感器的侦察模块、飞行驾驶漫游车模块和任务专用载荷模块组成。侦察模块负责绘制环境地图，并为能量感知规划器提供信息，该规划器联合选择路线和空地移动模式。漫游车和载荷模块能够独立飞越限制地面行驶的地形，然后自主组装成协作式地面车辆，以实现能量高效的载荷运输。受偏远且难以穿越区域环境采样的启发，我们通过涵盖感知、规划、重构、空地移动、载荷运输和任务执行的现场实验对HARP进行了评估。我们还在格陵兰冰盖上进行了模块级部署测试，以支持未来的自主任务。HARP展示了异构机器人团队不仅能够适应其行动，还能在任务过程中调整其物理能力的组合方式。

英文摘要

Heterogeneous robot teams distribute complementary capabilities across specialized agents, but their physical roles and capacities typically remain fixed throughout a mission. We present HARP, a Heterogeneous Aerial Robotic modules Platform in which independently deployable aerial robots physically reconfigure to compose their capabilities for field operations. HARP comprises sensor-equipped scouts, flydrive rover modules, and task-specific payload modules. Scouts map the environment and inform an energy-aware planner that jointly selects routes and air-ground mobility modes. Rover and payload modules fly independently across terrain that constrains ground travel, then autonomously assemble into a cooperative ground vehicle for energy-efficient payload transport. Motivated by environmental sampling in remote and difficult-to-traverse regions, we evaluate HARP through field experiments spanning sensing, planning, reconfiguration, airground mobility, payload transport, and task execution. We further conduct module-level deployment tests on the Greenland Ice Sheet toward future autonomous missions. HARP demonstrates how heterogeneous robot teams can adapt not only their actions, but also how their physical capabilities are composed during a mission.

发表机构

• Duke University（杜克大学）

机构由 AI 辅助整理，请以论文原文为准。