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The line coverage problem is the coverage of linear environment features (e.g., road networks, power lines), modeled as 1D segments, by one or more robots while respecting resource constraints (e.g., battery capacity, flight time) for each of the robots. The robots incur direction dependent costs and resource demands as they traverse the edges. We treat the line coverage problem as an optimization problem, with the total cost of the tours as the objective, by formulating it as a mixed integer linear program (MILP). The line coverage problem is NP-hard and hence we develop a heuristic algorithm, Merge- Embed-Merge (MEM). We compare it against the optimal MILP approach and a baseline heuristic algorithm, Extended Path Scanning. We show the MEM algorithm is fast and suitable for real-time applications. To tackle large-scale problems, our approach performs graph simplification and graph partitioning, followed by robot tour generation for each of the partitioned subgraphs. We demonstrate our approach on a large graph with 4,658 edges and 4,504 vertices that represents an urban region of about 16 sq. km. We compare the performance of the algorithms on several small road networks and experimentally demonstrate the approach using UAVs on the UNC Charlotte campus road network.
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This content will become publicly available on August 28, 2025
Multi-Objective Heuristics For Network Construction In An Obstacle-Dense Environment
We present a heuristic method to construct an optimal communication network in an obstacle-dense environment. A set of immobile terminals must be connected by a network of straight-line edges by adding agents to serve as relays. Obstacles are represented by polygons, unaccessible by the agents of the network or by the edges. The problem with obstacles is reduced to a problem without obstacles by choosing the nodes of the optimal network among the obstacles’ vertices that are in mutual line of sight. A second heuristic method is developed to solve the bicriteria optimization problem with number of agents and length of the network as concurrent costs.
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- PAR ID:
- 10552110
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-5851-3
- Page Range / eLocation ID:
- 838 to 845
- Subject(s) / Keyword(s):
- Costs Computer aided software engineering Automation Communication networks Relays Optimization
- Format(s):
- Medium: X
- Location:
- Bari, Italy
- Sponsoring Org:
- National Science Foundation
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