Development of Localization Technique using Trilateration Algorithm for E-Puck2 Robot

Topan Try Harmanda, K. Priandana, M. Hardhienata
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引用次数: 1

Abstract

This paper utilizes indoor localization techniques for E-Puck2 robots to assist the robot in locating their position in the predefined environment. The localization technique is crucial in many ways, one of which is in a multi-robot system to get accurate robot positions. In this paper, the Trilateration algorithm is utilized to locate E-Puck2 robot by using the value of Received Signal Strength Indication (RSSI) from Bluetooth Low Energy (BLE) beacons to indicate the distance between the robot and the beacons. Each beacon is placed in a certain position in the test environment and the RSSI value is calculated from the BLE signal. The RSSI value and position of the beacon are then sent to the server using a serial port to be processed by Trilateration algorithm so that the position of the robot can be obtained. The test is done in 2 scenarios, namely scenario 1, which uses three beacons and scenario 2, which uses four beacons. The average error in scenario 1 is 48.56±14.52 cm on the x-axis and 79.80±28.83 cm on the y-axis. Meanwhile, the average error in scenario 2 is 76.70±26.24 cm on the x-axis and 63.52±20.86 cm on the y-axis. These errors are mainly caused by uns table RSSI values, which depend on the environment and the robot’s heading. Although the produced error is quite high, the test results indicate that the localization technique using Trilateration algorithm can be implemented in both scenarios.
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E-Puck2机器人三边定位技术的发展
本文利用E-Puck2机器人的室内定位技术,帮助机器人在预定义的环境中定位自己的位置。定位技术在许多方面都是至关重要的,其中之一就是在多机器人系统中获得准确的机器人位置。本文采用Trilateration算法,利用蓝牙低功耗(Bluetooth Low Energy, BLE)信标的接收信号强度指示(Received Signal Strength Indication, RSSI)值来表示机器人与信标之间的距离,对E-Puck2机器人进行定位。将每个信标放置在测试环境中的一定位置,根据BLE信号计算RSSI值。然后将信标的RSSI值和位置通过串口发送到服务器,通过Trilateration算法进行处理,从而获得机器人的位置。测试在两个场景中完成,即场景1使用三个信标,场景2使用四个信标。场景1的x轴平均误差为48.56±14.52 cm, y轴平均误差为79.80±28.83 cm。同时,场景2的x轴平均误差为76.70±26.24 cm, y轴平均误差为63.52±20.86 cm。这些误差主要是由不确定的RSSI值引起的,RSSI值取决于环境和机器人的航向。虽然产生的误差相当大,但测试结果表明,使用Trilateration算法的定位技术可以在这两种情况下实现。
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