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首页> 外文期刊>Robotics and Autonomous Systems >Collaborative coverage using a swarm of networked miniature robots
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Collaborative coverage using a swarm of networked miniature robots

机译:使用大量联网微型机器人进行协作覆盖

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We study distributed coverage of environments with unknown extension using a team of networked miniature robots analytically and experimentally. Algorithms are analyzed by incrementally raising the abstraction level starting from physical robots, to realistic and discrete event system (DES) simulation. The realistic simulation is calibrated using sensor and actuator noise characteristics of the real platform and serves for calibration of the DES microscopic model. The proposed algorithm is robust to positional noise and communication loss, and its performance gracefully degrades for communication and localization failures to a lower bound, which is given by the performance of a non-coordinated, randomized solution. Results are validated by real robot experiments with miniature robots of a size smaller than 2 cm x 2 cm x 3 cm in a boundary coverage case study. Trade-offs between the abilities of the individual platform, required communication, and algorithmic performance are discussed.
机译:我们使用一组联网的微型机器人,通过分析和实验研究了未知扩展环境的分布式覆盖范围。从物理机器人到现实和离散事件系统(DES)仿真,通过逐步提高抽象级别来分析算法。使用真实平台的传感器和执行器噪声特性对真实仿真进行校准,并用于DES微观模型的校准。所提出的算法对位置噪声和通信损耗具有鲁棒性,并且由于通信和定位失败而性能下降到一个下限,这由非协调,随机解决方案的性能给出。在边界覆盖案例研究中,通过尺寸小于2 cm x 2 cm x 3 cm的微型机器人的真实机器人实验验证了结果。讨论了各个平台的功能,所需的通信和算法性能之间的折衷。

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