ION Alberta In-person Meeting – Thursday, 7 November 2024

We will have two speakers:

Meeting Theme: Smartphone Positioning

Rhea Zambra
Title: Smartphone HD Map Updates Using Monocular-Inertial ORB-SLAM3 and Gaussian Splatting


Abstract: Gaussian splatting has emerged as a state-of-the-art 3D representation technique due to its high-fidelity and fast rendering capabilities. While it has been successfully integrated into light detection and ranging (LiDAR) and depth-enabled simultaneous localization and mapping (SLAM) algorithms, its potential for accurate outdoor 3D mapping using smartphone data remains underexplored. Pre-built high definition (HD) maps are vital for autonomous vehicles but are costly to maintain, motivating research in decentralized, smartphone-enabled HD map update systems. Existing solutions lack direct 3D-to-3D point cloud comparison, which could offer more robust updates by bypassing segmentation-based object detection. In this paper, we present a novel post-processing pipeline that generates dense, accurate, and near-scale HD maps from smartphone data, enabling updates to existing LiDAR and multi-sensor generated base maps. Our approach uses monocular-inertial ORB-SLAM3 to recover a scaled camera trajectory, which uses loop-closure and keyframe selection to alleviate drift in the localization and point cloud reconstruction. The ORB-SLAM3 keyframes are then used to initialize a 3D Gaussian Splatting render of the scene, which densifies the point cloud using the images, and is then scaled by the monocular-inertial camera trajectory. The camera and IMU data are collected using an iPhone 14 Pro Max, at an outdoor loop at the University of Calgary that spans 158 meters. Both sensors are observed using the SensorLogger application, and the camera-IMU calibration is performed through Kalibr. This system results in a successful closed-loop 3D Gaussian render, producing a point cloud with 8.70% scale error and 0.493m root mean square (RMS) value for iterative closest point (ICP) when referenced to a LiDAR-IMU base map, showing the potential of smartphones in visual-inertial HD mapping. Additionally, the registration of a parked car demonstrates the system’s capability for accurate map updates when aligned with a LiDAR-based reference map.

Biography: Rhea Joyce Zambra is a M.Sc. student in the Department of Geomatics Engineering at the University of Calgary. She is part of the Intelligent Navigation and Mapping Lab, specializing in mapping and with research interest in the use of smartphones for accurate 3D reconstruction.

Naman Agarwal
Title: Application of Adaptive Kalman Filtering on Smartphone Positioning


Abstract: An Adaptive Kalman filter (AKF) is proposed which is used to estimate smartphone Global Navigation Satellite System (GNSS) pseudorange measurement variance. The filter is applied to stationary, bicycle and vehicle-based smartphone datasets collected in urban environments. The adaptive filter is compared to three other processing strategies: (i) conventional weighted least-squares, (ii) a velocity as random-walk Kalman filter (KF) for kinematic data or position as random-walk KF for static data, and (iii) an alternative KF implementation that uses Doppler to adapt process noise, all using a standard elevation and carrier-to-noise density ratio (C/N_0) measurement variance model. The adaptively estimated measurement variance is compared to the true error variance computed using the provided ground truth files and all four methods are evaluated in the position domain. The proposed AKF showed a horizontal positional accuracy improvement of 35.4%, 10.5%, and 27.3%, and a vertical positional accuracy improvement of 13.2%, 50.5%, and 59.6% for stationary, bicycle, and vehicle-based smartphone GNSS, respectively, compared to the second-best performing filter.

Biography: Naman Agarwal is a PhD student in the Department of Geomatics Engineering at the University of Calgary. He works in the PLAN lab under the supervision of Dr. Kyle O’Keefe. His main research area is “Precise Smartphone Positioning”.


Location: Room 207 – Engineering Block G (ENG), University of Calgary Campus

Date: Thursday November 7, 2024

Time: Doors will open at 11:30am, presentation beginning at noon
Cost: $20 non-members, $18 members, $15 grad students, undergrad students $10, includes a light lunch and refreshments. All proceeds go towards two annual scholarships for students attending the University of Calgary