Real-Time Performance Test of an Vision-based Inertial SLAM

Sukchang Yun,Byoung-Jin Lee,Young Jae Lee,Sangkyung Sung 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10

Despite its precise positioning performance, a GPS based navigation system may require the reference or augmentation station in close boundaries and is liable to be affected by satellite observation environments. Thus, this paper presents a vision-based inertial SLAM navigation system which can operate in a real-time manner and uses purely unknown feature points in order to cope with the limited GPS/INS integration environment. And real-time performance of the presented system is verified via indoor test.

Real-time Implementation of a Vision-aided Integrated Navigation System with a Tiny Vision Processing Camera Module

Sukchang Yun,Seung Jun Lee,Byoung-Jin Lee,Young Jae Lee,Sangkyung Sung 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10

This paper aims to implement a GPS/IMU/Vision sensor integrated navigation system which can operate in GPS-denied environments. This system is composed of a small and low-cost GPS, IMU and vision sensor. Both navigation filter and feature point tracking algorithm are loaded to Linux-based embedded processor for real-time operation. In this system, GPS/INS integrated filter and vision-based SLAM filter is used for navigation in that limited environment. With this navigation system outdoor flight test is carried out for proving its feasibility in unstructured environment.

A Normalized Measurement Vector Model for Enhancing Localization Performance of 6-DoF Bearing-only SLAM

Yun, Sukchang,Kim, Yeonjo,Lee, Byoungjin,Sung, Sangkyung Institute of Control, Robotics and Systems 2018 International Journal of Control, Automation, and Vol.16 No.2

This study proposes a novel bearing measurement model in order to improve the localization performance of 6-DoF SLAM (six degree-of-freedom simultaneous localization and mapping). The main limitation of the existing measurement model for 6-DoF bearing-only SLAM using feature points was first analyzed, and a bearing measurement normalization method was then presented in order to cope with this limitation. The existing measurement model has a vulnerability in that the bearing measurement has different error levels depending on the feature point position, and thus the validity of the model is degraded as the feature point moves closer to the origin in the image. This problem can cause the innovation vector to become abnormally large in extended Kalman filter (EKF)-based navigation filters, resulting in divergence of the navigation filter. The normalization method proposed in this study makes the measurement error level constant. The new measurement model was derived using this method, and a bearing-only SLAM consisting of an inertial measurement unit (IMU) and bearing sensors was constructed in the EKF framework. The validity of this measurement model was analyzed by checking the innovation vectors in the navigation filter, and the performance of the system was verified through simulations by comparing with the navigation solution based on the existing measurement model.

Integrated Navigation Design Using a Gimbaled Vision/LiDAR System with an Approximate Ground Description Model

Sukchang Yun,Young Jae Lee,Chang Joo Kim,Sangkyung Sung 한국항공우주학회 2013 International Journal of Aeronautical and Space Sc Vol.14 No.4

This paper presents a vision/LiDAR integrated navigation system that provides accurate relative navigation performance on a general ground surface, in GNSS-denied environments. The considered ground surface during flight is approximated as a piecewise continuous model, with flat and slope surface profiles. In its implementation, the presented system consists of a strapdown IMU, and an aided sensor block, consisting of a vision sensor and a LiDAR on a stabilized gimbal platform. Thus, two-dimensional optical flow vectors from the vision sensor, and range information from LiDAR to ground are used to overcome the performance limit of the tactical grade inertial navigation solution without GNSS signal. In filter realization, the INS error model is employed, with measurement vectors containing two-dimensional velocity errors, and one differenced altitude in the navigation frame. In computing the altitude difference, the ground slope angle is estimated in a novel way, through two bisectional LiDAR signals, with a practical assumption representing a general ground profile. Finally, the overall integrated system is implemented, based on the extended Kalman filter framework, and the performance is demonstrated through a simulation study, with an aircraft flight trajectory scenario.

Augmented Feature Point Initialization Method for Vision/Lidar Aided 6-DoF Bearing-Only Inertial SLAM

Yun, Sukchang,Lee, Byoungjin,Kim, Yeon-Jo,Lee, Young Jae,Sung, Sangkyung The Korean Institute of Electrical Engineers 2016 Journal of Electrical Engineering & Technology Vol.11 No.6

This study proposes a novel feature point initialization method in order to improve the accuracy of feature point positions by fusing a vision sensor and a lidar. The initialization is a process that determines three dimensional positions of feature points through two dimensional image data, which has a direct influence on performance of a 6-DoF bearing-only SLAM. Prior to the initialization, an extrinsic calibration method which estimates rotational and translational relationships between a vision sensor and lidar using multiple calibration tools was employed, then the feature point initialization method based on the estimated extrinsic calibration parameters was presented. In this process, in order to improve performance of the accuracy of the initialized feature points, an iterative automatic scaling parameter tuning technique was presented. The validity of the proposed feature point initialization method was verified in a 6-DoF bearing-only SLAM framework through an indoor and outdoor tests that compare estimation performance with the previous initialization method.

Range/Optical Flow-aided Integrated Navigation System in a Strapdown Sensor Configuration

Yun, Sukchang,Lee, Young Jae,Sung, Sangkyung Institute of Control, Robotics and Systems 2016 International Journal of Control, Automation, and Vol.14 No.1

This paper presents a measurement fusion mechanism of a strapdown range/vision sensor and IMU for an integrated navigation system in order to provide accurate relative navigation performance on a general ground surface in a GNSS-denied environment. The ground surface model during maneuvering is proposed as a piecewise continuous one, with flat and sloped surface profiles. In its implementation, the presented system consists of an IMU and the aided sensor modules, consisting of a vision sensor and a LiDAR. For obtaining improved performance of integrated navigation system, it is suggested a new measurement model and sensor fusion scheme incorporating two-dimensional flow vectors and range from aided sensors with inertial measurements. In filter realization, an indirect INS error model is employed, with measurement vectors containing two-dimensional velocity errors, and one differenced altitude in the navigation frame. In computing the altitude difference, the ground slope angle is estimated through two bisectional LiDAR signals, with a practical assumption representing a typical ground profile. In this process, the range variation due the attitude change of the system is compensated in a novel way, through geometric characteristics between range measurements and ground shape. Finally, the overall integrated system is implemented, based on the extended Kalman filter framework, and the performance is demonstrated through a simulation study with an aircraft flight trajectory scenario and experiments with an integrated hardware platform.

Integrated Navigation Design Using a Gimbaled Vision/LiDAR System with an Approximate Ground Description Model

Yun, Sukchang,Lee, Young Jae,Kim, Chang Joo,Sung, Sangkyung The Korean Society for Aeronautical and Space Scie 2013 International Journal of Aeronautical and Space Sc Vol.14 No.4

This paper presents a vision/LiDAR integrated navigation system that provides accurate relative navigation performance on a general ground surface, in GNSS-denied environments. The considered ground surface during flight is approximated as a piecewise continuous model, with flat and slope surface profiles. In its implementation, the presented system consists of a strapdown IMU, and an aided sensor block, consisting of a vision sensor and a LiDAR on a stabilized gimbal platform. Thus, two-dimensional optical flow vectors from the vision sensor, and range information from LiDAR to ground are used to overcome the performance limit of the tactical grade inertial navigation solution without GNSS signal. In filter realization, the INS error model is employed, with measurement vectors containing two-dimensional velocity errors, and one differenced altitude in the navigation frame. In computing the altitude difference, the ground slope angle is estimated in a novel way, through two bisectional LiDAR signals, with a practical assumption representing a general ground profile. Finally, the overall integrated system is implemented, based on the extended Kalman filter framework, and the performance is demonstrated through a simulation study, with an aircraft flight trajectory scenario.

Augmented Feature Point Initialization Method for Vision/Lidar Aided 6-DoF Bearing-Only Inertial SLAM

Sukchang Yun,Byoungjin Lee,Yeon-Jo Kim,Young Jae Lee,Sangkyung Sung 대한전기학회 2016 Journal of Electrical Engineering & Technology Vol.11 No.6

This study proposes a novel feature point initialization method in order to improve the accuracy of feature point positions by fusing a vision sensor and a lidar. The initialization is a process that determines three dimensional positions of feature points through two dimensional image data, which has a direct influence on performance of a 6-DoF bearing-only SLAM. Prior to the initialization, an extrinsic calibration method which estimates rotational and translational relationships between a vision sensor and lidar using multiple calibration tools was employed, then the feature point initialization method based on the estimated extrinsic calibration parameters was presented. In this process, in order to improve performance of the accuracy of the initialized feature points, an iterative automatic scaling parameter tuning technique was presented. The validity of the proposed feature point initialization method was verified in a 6-DoF bearing-only SLAM framework through an indoor and outdoor tests that compare estimation performance with the previous initialization method.

Design and Performance test of Relative Navigation of a low cost inertial SLAM

Sukchang Yun,Sangkyung Sung,Young Jae Lee 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8

Despite its precise positioning performance, a GPS based navigation system may require the reference or augmentation station in close boundaries and is liable to be affected by satellite observation environments. Thus, thispaper presents an INS/vision sensor integrated system, which in principle uses purely unknown feature points in previous epochs in order to cope with the limited GPS/INS integration environment. For the implementation ofthree-dimensional navigation using feature points, the presented system takes advantage of a robust image extraction and tracking algorithm, data association, and inertial SLAM filter algorithm. Finally, experimental results verified the performance of integrated navigation system, through which the performance enhancement in estimating relativeposition of the vehicle is demonstrated effectively.

vSLAM 보조 통합항법시스템 구현 및 무인 회전익기를 이용한 비행시험 성능분석

윤석창(Sukchang Yun),이병진(Byoung-Jin Lee),윤석환(Sukhwan Yun),이영재(Young Jae Lee),성상경(Sangkyung Sung) 한국항공우주학회 2011 韓國航空宇宙學會誌 Vol.39 No.4

본 논문은 vSLAM 보조 통합항법시스템을 구현하고 비행 실험을 통해 성능 분석을 수행한다. 구현한 항법시스템은 GPS 위성의 가시환경에 제한이 있는 지역에서의 일시적인 GPS 신호 두절 발생시, INS 단독 항법 수행으로 인한 위치 오차 발산을 vSLAM 보정을 통해 지연시킬 수 있다. 전동 헬기에 통합 시스템을 탑재하여 비행 실험을 수행하였고, 획득한 비행 데이터 중 임의로 GPS 신호가 제거된 특정 구간에서 INS 단독 항법과 INS/vSLAM 통합 항법간의 위치 추정 성능 비교를 통해 통합 시스템의 성능을 검증하였다. In this paper, vSLAM aided integrated navigation system is implemented and performance analysis of the system is completed via flight test. The system can suppress divergence of position error of INS only system by updating vSLAM correction information when temporary GPS signal outage occurs in bad radio condition. In the flight test, integrated hardware containing GPS, IMU and camera is loaded under RC electric helicopter. Performance of the integrated navigation system is verified by comparing estimated position of INS/vSLAM system with that of INS only system.