Mobile Robot Positioning with 433-MHz Wireless Motes with Varying Transmission Powers and a Particle Filter

Abstract

In wireless positioning systems, the transmitter's power is usually fixed. In this paper, we explore the use of varying transmission powers to increase the performance of a wireless localization system. To this extent, we have designed a robot positioning system based on wireless motes. Our motes use an inexpensive, low-power sub-1-GHz system-on-chip (CC1110) working in the 433-MHz ISM band. Our localization algorithm is based on a particle filter and infers the robot position by: (1) comparing the power received with the expected one; and (2) integrating the robot displacement. We demonstrate that the use of transmitters that vary their transmission power over time improves the performance of the wireless positioning system significantly, with respect to a system that uses fixed power transmitters. This opens the door for applications where the robot can localize itself actively by requesting the transmitters to change their power in real time.

Sistema de monitoreo de señales en tierra usando la Estación Terrena Satelital UPTC

“…El resumen fue formulado, tomando como referencia la revisión de casos de éxito en las áreas de Ciencias Agrícolas, Ciencias Médicas y de la Salud, Ciencias Naturales, Ciencias de la Educación, Ingeniería y Tecnología, con bandas de frecuencia compatibles y que podrían ser recibidas, procesadas y posteriormente compartidas desde la estación terrena satelital. tabla 2. resuMen de Monitoreo de variables eléctricas [25] Sistemas de localización inalámbrico para robot móviles [26] Sistema inalámbrico para medición de iluminación [27] Fuente: Autores.…”

Range-Only UWB SLAM for Indoor Robot Localization Employing Multi-Interval EFIR Rauch-Tung-Striebel Smoother

“…A new method of RFID system has been developed for localizing mobile robot employing configures reader (antenna) [13]. In [14], the WiFi has been used in mobile robot positioning. Noted that both the RFID and the WiFi are able to provide the position information in indoor environment, the localization accuracy of the RFID and the WiFi is not suitable for the high precision indoor mobile robot localization [15].…”

Accurate Position Estimation of Mobile Robot Based on Cyber-Physical-Social Systems (CPSS)

“…Therefore, the particle filter algorithm can be used to process the position data when performing state estimation of nonlinear system. For example, Adrian et al used wireless sensors and particle filter algorithms to improve the performance of position systems of mobile robot [25]. Gao et al used particle filter algorithm to realize path planning of mobile robot and improve the global adaptability of robot [26].…”

“…Hsu et al analyzed the signal characteristics and antenna effects of the received signal indicator, and designed a particle filter based on the current state of mobile robot to improve the positioning accuracy of the mobile robot in the wireless sensor network environment [27]. The literature [25]- [27] solve the problem of position estimation for nonlinear mobile robot system. However, the measurement data involved in estimating the position by using the particle filter algorithm is generally affected by the random errors by default, and did not consider the influence of the gross errors on the position estimation.…”