关于用于灾害管理的侦察自主机器人系统的调查
Sahaj Sinha1, Sinjae Lee2, Saurabh Singh1
1AI and Big Data, Endicott College, Woosong University, Daejeon 34606, Republic of Korea.
Sensors (Basel, Switzerland)
|March 14, 2026
概括
本次调查回顾了最新的灾难侦察机器人,强调了导航和传感器融合方面的进展. 在能源效率和这些无人地面车辆 (UGV) 的标准化基准方面仍然存在关键挑战.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 计算机视觉 计算机视觉
背景情况:
- 紧急情况需要在危险环境中运行的系统.
- 无人地面车辆 (UGV) 对于灾难侦察至关重要.
- 最近的进展重点是提高UGV的响应能力.
研究的目的:
- 为了调查地面灾难机器人技术的最新进展.
- 分析最近的UGV中的硬件,软件和自主性.
- 确定该领域的进展和剩余的挑战.
主要方法:
- 从2020-2025年对190多项研究进行了审查.
- 分析计算机视觉 (CV),机器学习 (ML) 和控制系统.
- 对LoRa通信,直流电机和双动力系统的评估.
主要成果:
- 在UGV导航,传感器融合和情境意识方面取得了显著进展.
- 在硬件,软件和自主性方面进行了改进,以应对灾害.
- 最近的研究表明,机器人系统的智能增强.
结论:
- 无人驾驶车在灾难侦察方面取得了明显的进步.
- 剩余的挑战包括能源使用和基准标准化.
- 未来的灾难应对系统需要解决方案,以提高稳定性和效率.
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