An Investigation Into Trajectory Estimation In Underground Mining Environments Using A Time-Of-Flight Camera And An Inertial Measurement Unit

Abstract

One of the most important and challenging tasks for mobile robots that navigate autonomously is localisation -the process whereby a robot locates itself within a map of a known environment or with respect to a known starting point within an unknown environment. Localisation of a robot in an unknown environment is done by tracking the trajectory of the robot on the basis of the initial pose. Trajectory estimation becomes a challenge if the robot is operating in an unknown environment that has a scarcity of landmarks, is GPS-denied, has very little or no illumination, and is slippery -such as in underground mines. This paper attempts to solve the problem of estimating a robot's trajectory in underground mining environments using a time-of-flight (ToF) camera and an inertial measurement unit (IMU). In the past, this problem has been addressed by using a 3D laser scanner; but these are expensive and consume a lot of power, even though they have high measurement accuracy and a wide field of view. Here, trajectory estimation is accomplished by the fusion of ego-motion provided by the ToF camera with measurement data provided by a low cost IMU. The fusion is performed using the Kalman filter algorithm on a mobile robot moving on a 2D planar surface. The results show a significant improvement on the trajectory estimation. A Vicon system is used to provide groundtruth for the trajectory estimation. Trajectory estimation only using the ToF camera is prone to errors, especially when the robot is rotating; but the fused trajectory estimation algorithm is able to estimate accurate ego-motion even when the robot is rotating. OPSOMMINGEen van die belangrikste en uitdagendste take vir mobiele robotte om selfstandig te kan navigeer is lokalisering. Lokalisering van 'n robot in 'n onbekende omgewing word gedoen deur die volg van die trajek van die robot (die aanvanklike posisie moet bekend wees). Trajekskatting raak uitdagend as die robot moet funksioneer in 'n onbekende omgewing met 'n tekort aan landmerke, geen GPS opvangs, baie swak of geen verligting en 'n gladde oppervlak -soos in ondergrondse myne. Hierdie artikel poog om die probleem van die skatting van 'n robot se trajek in ondergrondse mynbou omgewing met 'n tyd-van-vlug kamera en traagheid meet eenheid op te los. In die verlede is hierdie probleem aangespreek deur die gebruik van 'n 3D laserskandeerder. 3D laserskandeerders is duur en gebruik baie krag, al is hulle baie akkuraat met 'n wye veld van sig. In hierdie artikel is trajek skatting gedoen deur die samesmelting van die ego-beweging, gekry van die TVV kamera, en die meting data voorsien deur 'n goedkoop TME. Die samesmelting is uitgevoer deur gebruik te maak van die Kalmanfilter algoritme op 'n mobiele robot wat in 'n 2D plat vlak beweeg. Die resultate toon 'n verbetering op die trajekskatting. 'n Vicon stelsel word gebruik om die begin posisie te verskaf vir die trajekskatting. Trajekskatting slegs met die behulp van die TVV kamera is geneig tot foute, veral wanneer die robot draai. Die trajekskatting a...

A metrological characterization of the Kinect V2 time-of-flight camera

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Precise indoor localization and mapping using mobile laser scanners: a scoping review

“…Underground Mine (Ratshidaho et al 2014;Ghosh et al 2017b;Artan et al 2012; Zlot and Bosse2013) 5 21 Simulated environment (Fauser et al 2017;Ma et al 2016; 3 13 Lab/Corridor Shamseldin et al 2018;Niu et al 2017b;Ramer et al 2015;Baatar et al 2014;Tang et al 2014;Hu et al 2013;Wang et al 2011;Tamas et al 2009;Xu et al 2019;Shi et al 2018;Wang et al 2014;Guanglei et al 2014;Lee and Park2013;Keller and Sternberg2013) 14 58…”

“…WiFI/Beacon/RFID (Losch et al 2019;Shi et al 2018;Ma et al 2016) 3 12 Close-Loop (Losch et al 2019;Shamseldin et al 2018;Hu et al 2013;Wang et al 2014;Guanglei et al 2014;Lee and Park2013;Artan et al 2012;Zlot and Bosse2013) 9 38 Control points (Wang et al 2011;Xu et al 2019;Keller and Sternberg2013) 3 12 Reference Map (Losch et al 2019;Niu et al 2017b;Ramer et al 2015;Baatar et al 2014;Ratshidaho et al 2014;Ghosh et al 2017b;Ma et al 2016; 8 33…”

“…LiDAR (Losch et al 2019;Shamseldin et al 2018;Niu et al 2017b;Ramer et al 2015;Ratshidaho et al 2014;Hu et al 2013;Wang et al 2011;Tamas et al 2009;Xu et al 2019;Shi et al 2018;Ghosh et al 2017b;Ma et al 2016;Wang et al 2014;Guanglei et al 2014;Lee and Park2013;Keller and Sternberg2013;Artan et al 2012; Zlot and Bosse2013) 20 83 Odometer (Ramer et al 2015;Baatar et al 2014;Tang et al 2014;Hu et al 2013;Tamas et al 2009;Xu et al 2019;Zarei and Ramezani2018;Shi et al 2018;Fauser et al 2017;Ghosh et al 2017b;Ma et al 2016;Wang et al 2014;Guanglei et al 2014;Lee and Park2013;Keller and Sternberg2013;Artan et al 2012) 16 67 Camera (Losch et al 2019;Ramer et al 2015;Baatar et al 2014;Wang et al 2011;Fauser et al 2017;Lee and Park2013;Keller and Sternberg2013) 8 33…”

The use of geomatic techniques to improve the management of metro infrastructure

“…It is essential to set control points, patterns, or mixed systems that allow underground positioning. One of the latter systems consists of replacing TLS sensors with 3D ToF (Time of Flight) cameras (Ratshidaho et al, 2014).…”