多机器人协同探索未知3D环境，边查边传，通信受限下仍高效完成任务。
SLEI3D: Simultaneous Exploration and Inspection via Heterogeneous Fleets under Limited Communication
- 分层多速率规划，异构机器人分组协作，动态调整探索与检查策略。
- 48台机器人、38.4万立方米大场景仿真验证，硬件实验含7台机器人。
- 适用于无网络覆盖的复杂环境，适合应急搜救、地下巡检等场景。
无人机与地面机器人组成的异构机器人集群常用于静态环境的例行巡检，但许多应用中待查区域未知，需在探索过程中在线识别。本文研究在通信受限条件下，同时实现未知环境的协同3D探索、自适应详细检查及实时向移动控制站报告发现。异构机器人配备不同传感器：长距离激光雷达用于快速探索，近距离摄像头用于细节检查。由于全局通信通常不可用，机器人仅能在彼此靠近且无遮挡时通过自组网无线通信。为此，提出SLEI3D框架，集成在线协同3D探索、自适应检查与及时通信（采用间歇或主动协议）策略。针对特征数量与位置的不确定性，设计分层多速率规划机制，协调组内与组间局部计划。通过高达48台机器人、38.4万立方米的大规模高保真仿真进行广泛验证，并开展了7台机器人的硬件实验。项目网站见https://junfengchen-robotics.github.io/SLEI3D/。
原文摘要 · Abstract (English)
Robotic fleets such as unmanned aerial and ground vehicles have been widely used for routine inspections of static environments, where the areas of interest are known and planned in advance. However, in many applications, such areas of interest are unknown and should be identified online during exploration. Thus, this paper considers the problem of simultaneous exploration, inspection of unknown environments and then real-time communication to a mobile ground control station to report the findings. The heterogeneous robots are equipped with different sensors, e.g., long-range lidars for fast exploration and close-range cameras for detailed inspection. Furthermore, global communication is often unavailable in such environments, where the robots can only communicate with each other via ad-hoc wireless networks when they are in close proximity and free of obstruction. This work proposes a novel planning and coordination framework (SLEI3D) that integrates the online strategies for collaborative 3D exploration, adaptive inspection and timely communication (via the intermit-tent or proactive protocols). To account for uncertainties w.r.t. the number and location of features, a multi-layer and multi-rate planning mechanism is developed for inter-and-intra robot subgroups, to actively meet and coordinate their local plans. The proposed framework is validated extensively via high-fidelity simulations of numerous large-scale missions with up to 48 robots and 384 thousand cubic meters. Hardware experiments of 7 robots are also conducted. Project website is available at https://junfengchen-robotics.github.io/SLEI3D/.
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