$\epsilon^{\star}+$: An Online Coverage Path Planning Algorithm for Energy-constrained Autonomous Vehicles

Shen, Zongyuan; Wilson, James P.; Gupta, Savita

doi:10.1109/ieeeconf38699.2020.9389353

Cited by 9 publications

(3 citation statements)

References 17 publications

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“…This strategy results in shorter trajectory lengths compared to classical methods based on back-and-forth motions. Shen et al (2020) extended it recently by adding energy constraints. The robot executes the coverage path until its energy is low; then, it returns to the charging station to refill its battery.…”

Section: Related Workmentioning

confidence: 99%

Unknown area exploration for robots with energy constraints using a modified Butterfly Optimization Algorithm

Bendahmane

Tlemsani²

2022

Soft Comput

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Butterfly Optimization Algorithm (BOA) is a recent metaheuristic that has been used in several optimization problems. In this paper, we propose a new version of the algorithm (xBOA) based on the crossover operator and compare its results to the original BOA and 3 other variants recently introduced in the literature. We also proposed a framework for solving the unknown area exploration problem with energy constraints using metaheuristics in both single-and multi-robot scenarios. This framework allowed us to benchmark the performances of different metaheuristics for the robotics exploration problem. We conducted several experiments to validate this framework and used it to compare the effectiveness of xBOA with wellknown metaheuristics used in the literature through 5 evaluation criteria. Although BOA and xBOA are not optimal in all these criteria, we found that BOA can be a good alternative to many metaheuristics in terms of the exploration time, while xBOA is more robust to local optima; has better fitness convergence; and achieves better exploration rates than the original BOA and its other variants.

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Section: Related Workmentioning

confidence: 99%

Unknown area exploration for robots with energy constraints using a modified Butterfly Optimization Algorithm

Bendahmane

Tlemsani²

2022

Soft Comput

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“…Some literature presented possible methods to solve this problem. Shen et al developed the ε*+ algorithm [12], an extension of the ε* algorithm for the online CPP of unmanned vehicles with energy constraints. The mean feature of this work is that the robot would go back to the base to recharge when its battery runs low.…”

Section: Introductionmentioning

confidence: 99%

“…After recharging, the robot would continue its work from where it stopped. An example of this method is the ε*+ algorithm presented by Shen et al [12]. This algorithm extends the ε* algorithm presented by Song and Gupta [10] and the main feature of it is that the robot would retreat to its recharging station when the battery runs low.…”

Section: Introductionmentioning

confidence: 99%

An adaptive coverage path planning method considering energy constraints

Shao

2023

Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022)

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Coverage path planning algorithms are widely used by many robots conducting work like floor sweeping, map generating and underwater searching. One of the practical methods is the Backtracking Spiral Algorithm (BSA), which is efficient and complete coverage guaranteed. In practice, however, autonomous robots are faced with the problem of energy constraints. The duration of the battery of a robot is usually limited. This paper presents an adaptive coverage path planning method based on BSA considering the energy constraints. The objective of this method is to minimise the total length of the path the robot travelled to recharge while guaranteeing complete coverage. This method uses an estimation strategy which would use the energy consumption of the last round as a conjecture of that of the next round and recharge when the remaining energy would probably be insufficient to complete the next round while the robot passes nearby the recharging station. A simulation result is then provided to serve as proof of this method.

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Hybrid Boustrophedon and Partition Tree Group Algorithm for Coverage Path Planning Problem with Energy Constraints

Giang

Bình

2022

Communications in Computer and Information Science

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$\epsilon^{\star}+$: An Online Coverage Path Planning Algorithm for Energy-constrained Autonomous Vehicles

Cited by 9 publications

References 17 publications

Unknown area exploration for robots with energy constraints using a modified Butterfly Optimization Algorithm

Unknown area exploration for robots with energy constraints using a modified Butterfly Optimization Algorithm

An adaptive coverage path planning method considering energy constraints

Hybrid Boustrophedon and Partition Tree Group Algorithm for Coverage Path Planning Problem with Energy Constraints

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