SLEI3D: Simultaneous Exploration and Inspection via Heterogeneous Fleets Under Limited Communication
🤖 AI Summary
This work addresses the challenge of efficiently coordinating heterogeneous robots for exploration, detection, and real-time data transmission in unknown environments where global communication is unavailable and only short-range ad hoc networking is supported. The authors propose SLEI3D, a novel framework featuring a unified planning architecture that integrates collaborative 3D exploration, adaptive object detection, and an intermittent active communication strategy. To handle environmental uncertainty and sensor heterogeneity—such as differences between long-range LiDAR and short-range cameras—the system employs a multi-layer, multi-rate decision-making mechanism. Leveraging proximity-based ad hoc networking and dynamic task allocation, SLEI3D demonstrates significantly improved collaborative efficiency in both large-scale high-fidelity simulations (involving 48 robots across 384,000 m³) and real-world experiments with seven physical robots, validating its effectiveness and scalability.
Application Category
📝 Abstract
Robotic fleets such as uncrewed 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 intermittent 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. Note to Practitioners—This paper is motivated by the challenges of coordinating large-scale heterogeneous fleets for the inspection of large buildings and infrastructure, where heterogeneous UAVs must collaborate to explore unknown environments, identify areas of interest, and more importantly, inspect specific features (such as cracks, leaks, and other anomalies). Furthermore, these features must be relayed back to a control station for further analyses. Existing methods predominantly focuses on exploration tasks and often overlooks the need for close-up inspection. Instead, a hierarchical and flexible framework is proposed to coordinate a group of heterogeneous UAVs online for efficient exploration, inspection and communication, subject to an unknown number and location of features. Instead of relying on an all-to-all communication network, limited communication range and bandwidth are addressed by leveraging intermittent and proactive communication protocols, i.e., to enable exchange of local plans, explored areas, and detected features during online execution. Via extensive simulations in a high-fidelity simulator, the proposed framework is shown to be efficient and reliable for large-scale simultaneous exploration and inspection tasks within various scenes. Robustness to robot failures and communication loss is also demonstrated. Hardware experiments over UGVs and UAVs validate the practical relevance.
Problem
Research questions and friction points this paper is trying to address.
simultaneous exploration and inspection
heterogeneous robotic fleets
limited communication
unknown environments
real-time reporting
Innovation
Methods, ideas, or system contributions that make the work stand out.
heterogeneous robotic fleets
simultaneous exploration and inspection
limited communication
multi-layer multi-rate planning
3D autonomous coordination
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