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NeRF-VINS: A Real-time Neural Radiance Field Map-based Visual-Inertial Navigation System
Effectively leveraging NeRF’s potential to synthesize
novel views, essential for addressing limited viewpoints, the
proposed NeRF-VINS optimally fuses IMU and monocular
image measurements along with synthetically rendered images
within an efficient filter-based framework, 2023
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MINS: Efficient and Robust Multisensor-aided Inertial Navigation System
A consistent tightly coupled Multisensor-aided Inertial Navigation System (MINS) that is capable of fusing the most common navigation
sensors. Support:
- An efficient and robust filtering-based multi-sensor estimator
- Fuse IMU, wheel encoders, cameras, LiDARs, and GPS
- Flexible in adding homogenous and heterogeneous sensors
- Online calibration of all onboard sensors extrinsic and intrinsic
- Handle asynchronous and delayed measurements
- Lightweight with on-manifold state interpolation and dynamic cloning
- Resilient to sensor failures, measurement depletion, and outliers
- Robust proprioceptive sensor-based initialization
- Sensor simulation toolbox for algorithm evaluation
2023
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Optimization-based VINS: Consistency, Marginalization, and FEJ
A comprehensive analysis
of the application of the First-estimates Jacobian (FEJ) design
methodology in nonlinear optimization-based Visual-Inertial
Navigation Systems (VINS), 2023
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Monocular Visual-Inertial Odometry with Planar Regularities
A novel real-time monocular VIO system that is fully regularized by planar features within a lightweight multi-state constraint Kalman filter (MSCKF), 2023
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Visual-Inertial-Aided Online MAV System Identification
An online MAV system identification algorithm
to tightly fuse visual, inertial and MAV aerodynamic information within a lightweight multi-state constraint Kalman filter
(MSCKF) framework, 2022
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Tightly-coupled GNSS-aided Visual-Inertial Localization
A tightly-coupled GNSS-aided visual-inertial navigation system which is able to leverage the complementary sensing modality from a visual-inertial sensing pair,
which provides high-frequency local information, and a GNSS receiver with low-frequency global observations, 2022
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Decoupled Right Invariant Error States for Consistent
Visual-Inertial Navigation
Two novel algorithms which
preserve the system consistency by leveraging the invariant state
representation and ensure efficiency by decoupling features from
covariance propagation, 2022
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Efficient multi-sensor aided inertial navigation with online calibration
A versatile multi-sensor aided inertial navigation system that can efficiently fuse multi-modal measurements of IMU, camera, wheel encoder, GPS, and 3D LiDAR along with online spatiotemporal sensor calibration.
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iCalib: Inertial Aided Multi-Sensor Calibration
A holistic non-linear least squares
(NLS) based multi-sensor calibration system, which exploits
high-rate inertial navigation and can handle a multitude of
asynchronous sensors commonly found on robots (e.g., IMU,
cameras, LiDARs, and wheel odometry) while requiring only
initial calibration guesses, 2021
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OpenVINS: A Research Platform for Visual-Inertial Estimation
An open platform, termed OpenVINS, for visual-inertial estimation research. Supports:
- On-manifold sliding window Kalman filter
- Online IMU/camera intrinsic and extrinsic calibration
- Camera to inertial sensor time offset calibration
- SLAM landmarks with different representations and consistent FEJ
- Modular type system for state management
- Extendable visual-inertial system simulator
- Extensive toolbox for algorithm evaluation 2020
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Versatile 3D Multi-Sensor Fusion for Lightweight 2D Localization
A 2-stage localization system which incorporates both offline prior map building and
online multi-modal localization. In particular, we develop an
occupancy grid mapping system with probabilistic odometry
fusion, accurate scan-to-submap covariance modeling, and
accelerated loop-closure detection, which is further aided by
2D line features that exploit the environmental structural
constraints, 2020
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Visual-Inertial-Wheel Odometry with Online Calibration
A novel visual-inertialwheel odometry (VIWO) system for ground vehicles, which
efficiently fuses multi-modal visual, inertial and 2D wheel
odometry measurements in a sliding-window filtering fashion.
Wheel encoders’ both intrinsic and extrinsic (spatiotemproal) parameters are calibrated online, 2020
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Intermittent GPS-aided VIO: Online Initialization and Calibration
An efficient and robust GPS-aided visual inertial odometry (GPS-VIO) system that fuses IMU-camera data with intermittent GPS measurements.
To perform sensor fusion, spatiotemporal sensor calibration and initialization of the transform between the sensor reference frames are addressed, 2020
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OpenVINS: A Research Platform for Visual-Inertial Estimation
The open
sourced codebase provides a foundation for researchers and
engineers to quickly start developing new capabilities for their
visual-inertial systems, 2019
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LIC-Fusion: LiDAR-Inertial-Camera Odometry
A tightly-coupled multi-sensor fusion algorithm termed LiDAR-inertial-camera fusion (LIC-Fusion), which efficiently fuses IMU measurements, sparse visual features, and extracted LiDAR points, 2019
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Practical Modeling of GNSS for Autonomous Vehicles in Urban Environments
A method of quantitatively modeling uncertainty in the accumulated GNSS and in wheel encoder data accumulated in anonymous urban environments, collected using vehicles, 2019
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Position estimation using multiple low-cost GPS receivers for outdoor mobile robots
A method of using multiple low-cost GPS
receivers in position estimation to enhance accuracy and
decrease system buildup cost, 2015
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A Big Data System Design to Predict the Vehicle Slip
A system storing sensor data generated from the vehicle using Big data system and
analyzing real-time sensor output to predict the car slip, 2015
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