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Line Coverage With Multiple Robots: Algorithms and Experiments
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AI
DOI：10.1109/TRO.2024.3355802.png)
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Abstract
En 中文
The line coverage problem involves finding efficient routes for the coverage of linear features by one or more resource-constrained robots. Linear features model environments such as road networks, power lines, and oil and gas pipelines. Two modes of travel are defined for robots: servicing and deadheading. A robot services a feature if it performs task-specific actions, such as taking images, as it traverses the feature; otherwise, it is deadheading. Traversing the environment incurs costs (e.g., travel time) and resource demands (e.g., battery life). Servicing and deadheading can have different cost and demand functions, which can be direction dependent. The environment is modeled as a graph, and an integer linear program is presented. As the problem is NP-hard, we design a fast and efficient heuristic algorithm, Merge-Embed-Merge (MEM). Exploiting the constructive property of the MEM algorithm, algorithms for line coverage of large graphs with multiple depots are developed. Furthermore, turning costs and nonholonomic constraints are efficiently incorporated into the algorithm. The algorithms are benchmarked on 100 road networks and demonstrated in experiments with aerial robots.
Keywords:
Aerial systems
applications
arc routing problems (ARPs)
motion and path planning
path planning for multiple mobile robots or agents
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