
This research paper proposes a novel keyframe sampling optimization method for LiDAR-based place recognition that minimizes redundancy while preserving essential information, leading to more efficient and reliable place recognition for robotic applications.


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keyframe-sampling-optimization-for-lidar-based-place-recognition-minimizing-redundancy-and-preserving-information-


Keyframe Sampling Optimization for LiDAR-based Place Recognition: Minimizing Redundancy and Preserving Information


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LiDAR-based place recognition systems are evaluated and deployed in dense forest environments, showcasing their performance and potential applications.


evaluation-and-deployment-of-lidar-based-place-recognition-in-dense-forests


Evaluation and Deployment of LiDAR-based Place Recognition in Dense Forests
