Using 6 DOF vision-inertial tracking to evaluate and improve low cost depth sensor based SLAM

Calloway, Thomas; Megherbi, Dalila B.

doi:10.1109/civemsa.2016.7524314

Cited by 2 publications

(3 citation statements)

References 18 publications

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“…On the other hand, given that the accuracy of SLAM is based on the precision of sensors, and the precision is sometimes related to the price of sensors, several researches are focus on how to cost down patrol systems [10][11][12][13][14][15][16][17][18][19][20][21][22][23]. Jiang, G. et al propose a graph optimization-based SLAM framework through combining a low-cost LiDAR and an RGB-D camera to improve the defect of accumulated error for building large maps only by low-cost LiDAR [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

“…Same for in order to reduce the cost of using high prices LiDAR, Jiang, G. et al propose a fast Fourier transform-based scan-match method to enhance the accuracy and resolution of a low-cost LiDAR [14]. Moreover, Shuda L. used only an RGB-D camera to realize the SLAM application [15][16][17]. For more, Gong Z. et al combine a cheap LiDAR system and crash sensors with a NVIDIA Jetson tk1 module on a wheeling robot to fabricate a low cost patrolling platform, and using tiny SLAM algorithm on the platform to achieve a real-time indoor mapping [18].…”

Section: Introductionmentioning

confidence: 99%

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Development of a Low Cost and Path-free Autonomous Patrol System Based on Stereo Vision System and Checking Flags

Lan

Chang

2020

Applied Sciences

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Nowadays, security guard patrol services are becoming roboticized. However, high construction prices and complex systems make patrol robots difficult to be popularized. In this research, a simplified autonomous patrolling robot is proposed, which is fabricated by upgrading a wheeling household robot with stereo vision system (SVS), radio frequency identification (RFID) module, and laptop. The robot has four functions: independent patrolling without path planning, checking, intruder detection, and wireless backup. At first, depth information of the environment is analyzed through SVS to find a passable path for independent patrolling. Moreover, the checkpoints made with RFID tag and color pattern are placed in appropriate positions within a guard area. While a color pattern is detected by the SVS, the patrolling robot is guided to approach the pattern and check its RFID tag. For more, the human identification function of SVS is used to detect an intruder. While a skeleton information of the human is analyzed by SVS, the intruder detection function is triggered, then the robot follows the intruder and record the images of the intruder. The recorded images are transmitted to a server through Wi-Fi to realize the remote backup, and users can query the recorded images from the network. Finally, an experiment is made to test the functions of the autonomous patrolling robot successfully.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development of a Low Cost and Path-free Autonomous Patrol System Based on Stereo Vision System and Checking Flags

Lan

Chang

2020

Applied Sciences

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“…Even though accuracy and precision have lesser importance for VR environments unlike tracking for localization [14], resolution of less than 1 mm and angular precision of greater than 0.2 degrees is important for VR applications. Tracking latency beyond 40-60 ms will also affect the performance of the VR [15].…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost, Wearable Opto-Inertial 6-DOF Hand Pose Tracking System for VR

et al. 2017

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Abstract:In this paper, a low cost, wearable six Degree of Freedom (6-DOF) hand pose tracking system is proposed for Virtual Reality applications. It is designed for use with an integrated hand exoskeleton system for kinesthetic haptic feedback. The tracking system consists of an Infrared (IR) based optical tracker with low cost mono-camera and inertial and magnetic measurement unit. Image processing is done on LabVIEW software to extract the 3-DOF position from two IR targets and Magdwick filter has been implemented on Mbed LPC1768 board to obtain orientation data. Six DOF hand tracking outputs filtered and synchronized on LabVIEW software are then sent to the Unity Virtual environment via User Datagram Protocol (UDP) stream. Experimental results show that this low cost and compact system has a comparable performance of minimal Jitter with position and orientation Root Mean Square Error (RMSE) of less than 0.2 mm and 0.15 degrees, respectively. Total Latency of the system is also less than 40 ms.

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Using 6 DOF vision-inertial tracking to evaluate and improve low cost depth sensor based SLAM

Cited by 2 publications

References 18 publications

Development of a Low Cost and Path-free Autonomous Patrol System Based on Stereo Vision System and Checking Flags

Development of a Low Cost and Path-free Autonomous Patrol System Based on Stereo Vision System and Checking Flags

A Low-Cost, Wearable Opto-Inertial 6-DOF Hand Pose Tracking System for VR

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