HMS-RRT: A novel hybrid multi-strategy rapidly-exploring random tree algorithm for multi-robot collaborative exploration in unknown environments

Ning, Yuming; Li, Tuanjie; Yao, Cong; Du, Wenqian; Zhang, Yan

doi:10.1016/j.eswa.2024.123238

Cited by 2 publications

(2 citation statements)

References 28 publications

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“…The mean values and standard divination of ET, PD, and total PD are presented in Table 1. The simulation is designed to replicate the methodology outlined in the simulation scenario 1 from Ning et al [15], facilitating a direct comparison of results between our method and theirs. The comparative results are shown in Table 2.…”

Section: Multi-robot Resultsmentioning

confidence: 99%

“…In [14], local and global RRT-based detectors are used for multi-robot exploration. Additionally, [15] proposes a novel frontier detection algorithm called Hybrid Multi-Strategy RRT to improve the efficiency and reliability of multi-robot exploration. Their method consists of an adaptive incremental distance strategy, a sub-region sampling strategy, and a greedy frontier-based exploration strategy.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Robot Exploration Employing Harmonic Map Transformations

Blounas,

Bechlioulis

2024

Applied Sciences

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Robot Exploration can be used to autonomously map an area or conduct search missions in remote or hazardous environments. Using multiple robots to perform this task can improve efficiency for time-critical applications. In this work, a distributed method for multi-robot exploration using a Harmonic Map Transformation (HMT) is presented. We employ SLAM to construct a map of the unknown area and utilize map merging to share terrain information amongst robots. Then, a frontier allocation strategy is proposed to increase efficiency. The HMT is used to safely navigate the robots to the frontiers until the exploration task is complete. We validate the efficacy of the proposed strategy via tests in simulated and real-world environments. Our method is compared to other recent schemes for multi-robot exploration and is shown to outperform them in terms of total path distance.

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Section: Multi-robot Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%