体积占用检测：建图算法的比较分析
Volumetric Occupancy Detection: A Comparative Analysis of Mapping Algorithms
AI总结：
本文针对协作机器人安全中的体积占用检测，构建仿真评估流程，系统比较 OctoMap、SkiMap 和 Voxblox 三种建图算法及其参数影响，为框架选择提供定性与定量依据。
摘要：
尽管人们对协作机器人创新功能的兴趣日益增长，体积检测对于确保基本安全仍然不可或缺。然而，目前缺乏专门针对该领域且被广泛使用的体积检测框架，现有评估指标主要关注时间和内存效率。为弥补这一不足，作者利用仿真环境、真值提取和自动化评估指标计算进行了详细比较。这使得能够评估最先进的体积建图算法，包括 OctoMap、SkiMap 和 Voxblox，并通过定性和定量分析的影响提供有价值的见解和比较。该研究不仅比较了不同框架，还探索了每个框架内的各种参数，为它们的性能提供了更多见解。
英文摘要：
Despite the growing interest in innovative functionalities for collaborative robotics, volumetric detection remains indispensable for ensuring basic security. However, there is a lack of widely used volumetric detection frameworks specifically tailored to this domain, and existing evaluation metrics primarily focus on time and memory efficiency. To bridge this gap, the authors present a detailed comparison using a simulation environment, ground truth extraction, and automated evaluation metrics calculation. This enables the evaluation of state-of-the-art volumetric mapping algorithms, including OctoMap, SkiMap, and Voxblox, providing valuable insights and comparisons through the impact of qualitative and quantitative analyses. The study not only compares different frameworks but also explores various parameters within each framework, offering additional insights into their performance.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
