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引用次数: 27

摘要

为了结合来自分布式机器人团队的传感器信息,了解所有机器人相对于彼此的位置是至关重要的。本文提出了一种新的用于厘米级机器人的容错定位算法。为了确定它们的位置,Millibots用超声波距离传感器测量它们之间的距离。然后,他们将这些距离测量与航位推算结合在一个最大似然估计器中。本文的重点是对定位系统中常见的测量故障进行检测和隔离。这些故障包括机器人与未检测到的障碍物碰撞时的航位推算误差,以及由于直接和多路径超声波阵面之间的破坏性干扰而导致的距离测量误差。仿真结果表明,该容错算法能够准确地检测出测量误差,显著提高了定位系统的可靠性和精度。
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Fault tolerant localization for teams of distributed robots
To combine sensor information from distributed robot teams, it is critical to know the locations of all the robots relative to each other. This paper presents a novel fault tolerant localization algorithm developed for centimeter-scale robots, called Millibots. To determine their locations, the Millibots measure the distances between themselves with an ultrasonic distance sensor. They then combine these distance measurements with dead reckoning in a maximum likelihood estimator. The focus of this paper is on detecting and isolating measurement faults that commonly occur in this localization system. Such failures include dead reckoning errors when the robots collide with undetected obstacles, and distance measurement errors due to destructive interference between direct and multi-path ultrasound wavefronts. Simulations show that the fault tolerance algorithm accurately detects erroneous measurements and significantly improves the reliability and accuracy of the localization system.
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