Heuristic Search for Path Finding With Refuelling

This letter considers a generalization of the Path Finding (PF) problem with refuelling constraints referred to as the Gas Station Problem (GSP). Similar to PF, given a graph where vertices are gas stations with known fuel prices, and edge costs are the gas consumption between the two vertices, GSPs...

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Vydáno v:IEEE robotics and automation letters Ročník 10; číslo 4; s. 3230 - 3237
Hlavní autoři: Zhao, Shizhe, Nandy, Anushtup, Choset, Howie, Rathinam, Sivakumar, Ren, Zhongqiang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.04.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Apexes
Autonomous aerial vehicles
Costs
Dynamic programming
Fuels
Graph theory
Heuristic
Mathematical programming
Motion and path planning
Motion planning
Path planning
Polynomials
Refueling
Robot kinematics
robotics in under-resourced settings
Runtime
scheduling and coordination
Search algorithms
Service stations
Training
Urban areas
ISSN:2377-3766, 2377-3766
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Shrnutí:This letter considers a generalization of the Path Finding (PF) problem with refuelling constraints referred to as the Gas Station Problem (GSP). Similar to PF, given a graph where vertices are gas stations with known fuel prices, and edge costs are the gas consumption between the two vertices, GSPseeks a minimum-cost path from the start to the goal vertex for a robot with a limited gas tank and a limited number of refuelling stops. While GSPis polynomial-time solvable, it remains a challenge to quickly compute an optimal solution in practice since it requires simultaneously determine the path, where to make the stops, and the amount to refuel at each stop. This letter develops a heuristic search algorithm called <inline-formula><tex-math notation="LaTeX">\text{Refuel A}^*</tex-math></inline-formula> (<inline-formula><tex-math notation="LaTeX">\text{RF-A}^*</tex-math></inline-formula>) that iteratively constructs partial solution paths from the start to the goal guided by a heuristic while leveraging dominance rules for pruning during planning. <inline-formula><tex-math notation="LaTeX">\text{RF-A}^*</tex-math></inline-formula>is guaranteed to find an optimal solution and often runs 2 to 8 times faster than the existing approaches in large city maps with several hundreds of gas stations.
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ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2025.3540736