December 8, 2025Unmanned Systems

Unmanned Vehicle Unknown Environment Exploration Algorithm Based on Motion Primitives

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Authors

SWShaobin WuBeijing Institute of Technology YHYu HuangShanghai Pudong New Area Gongli Hospital

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Implication

This algorithm improves target detection and navigation efficiency in unmanned ground vehicles, highlighting capabilities in autonomous exploration and obstacle avoidance.

Key Points

Robust path planning algorithm enhances target detection in unknown environments, achieving 99 ms average planning time.
The approach reduces expanded nodes to 1.38% of baseline, with real-vehicle tests showing 0.327 m localization error.
Real-time perception integrates LiDAR and GNSS data to support navigation under nonholonomic constraints.
Supports search-and-rescue missions by facilitating efficient autonomous exploration strategies.

Cite This Study

Wu et al. (2025) studied this question.

synapsesocial.com/papers/693624ad4fa91c937236c69b https://doi.org/10.1142/s230138502750052x

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Implication

This algorithm improves target detection and navigation efficiency in unmanned ground vehicles, highlighting capabilities in autonomous exploration and obstacle avoidance.

Unmanned Vehicle Unknown Environment Exploration Algorithm Based on Motion Primitives

Discussion

Member takes

Implication

Key Points

Cite This Study

Unmanned Vehicle Unknown Environment Exploration Algorithm Based on Motion Primitives

Discussion

Member takes

Implication

Key Points

Cite This Study

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