Pose Estimation with Dual Quaternions and Iterative Closest Point

Sveier, Aksel; Myhre, Torstein A.; Egeland, Olav

doi:10.23919/acc.2018.8431077

Cited by 4 publications

(2 citation statements)

References 22 publications

(38 reference statements)

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“…In addition, they offer the most compact way to represent rotations and translations. More recently, they have been employed in visual SLAM techniques based on stochastic filters [ 40 , 41 , 42 , 43 , 44 , 45 ], and some based on graph-SLAM [ 46 , 47 ] have been observed. Despite the wide use of this parametrization in feature-based SLAM approaches, our approach is the first to use it in direct VO.…”

Section: Related Workmentioning

confidence: 99%

DPO: Direct Planar Odometry with Stereo Camera

Lins

Rosa

Grassi

et al. 2023

Sensors

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Nowadays, state-of-the-art direct visual odometry (VO) methods essentially rely on points to estimate the pose of the camera and reconstruct the environment. Direct Sparse Odometry (DSO) became the standard technique and many approaches have been developed from it. However, only recently, two monocular plane-based DSOs have been presented. The first one uses a learning-based plane estimator to generate coarse planes as input for optimization. When these coarse estimates are too far from the minimum, the optimization may fail. Thus, the entire system result is dependent on the quality of the plane predictions and restricted to the training data domain. The second one only detects planes in vertical and horizontal orientation as being more adequate to structured environments. To the best of our knowledge, we propose the first Stereo Plane-based VO inspired by the DSO framework. Differing from the above-mentioned methods, our approach purely uses planes as features in the sliding window optimization and uses a dual quaternion as pose parameterization. The conducted experiments showed that our method presents a similar performance to Stereo DSO, a point-based approach.

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Section: Related Workmentioning

confidence: 99%

DPO: Direct Planar Odometry with Stereo Camera

Lins

Rosa

Grassi

et al. 2023

Sensors

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“…Since we assume that the object is always in the field of view of the 3-D camera, we can expect that states with high likelihood will result in model point clouds M i k+1 that are in the field of view. We can then project the model point clouds to the camera image plane, using the intrinsic camera calibration matrix K , and perform the NN-search in the depth image of the measured point cloud, similar to our previous work [30]. The NN-search is performed with a radius r around the pixel position of a point m i j,k+1 ∈ M i k+1 .…”

Section: Implementation Considerationsmentioning

confidence: 99%

Dual Quaternion Particle Filtering for Pose Estimation

Sveier

Egeland

2021

IEEE Trans. Contr. Syst. Technol.

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This article presents a particle filter for pose estimation using unit dual quaternion kinematics. The eight-parameter unit dual quaternion is used for global representation of the pose, whereas the six parameters of the dual modified Rodrigues parameters (MRPs) are used for local pose representation in the state-space model. The dual MRPs enable estimates of the mean and the covariance to be calculated from the particles without violating the algebraic constraint of the unit dual quaternion. For verification of the filter and comparison with state of the art, we consider pose measurements available in the form of unit dual quaternions. Angular velocity and specific force measurements from a body-mounted inertial measurement unit are also considered in the filtering. We show through simulations that the suggested particle filter has comparable accuracy with a previously proposed unscented Kalman filter based on unit dual quaternions. We also consider a practical application where the pose of an arbitrary rigid object is estimated using a sequence of point clouds from a 3-D camera. A model point cloud of the object is displaced with the unit dual quaternion associated with each particle, and a fitting score is calculated between the displaced model point cloud and the measured point cloud from the 3-D camera. The likelihoods of the fitting scores are calculated from an exponential distribution and are used to update the weights of the particles. The system was verified in an experiment where the motion of a swinging payload hanging from a crane was estimated using a 3-D camera.

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Vision Based Robust Pose Estimation Using Multiplicative Extended Kalman Filter and Iterative Closest Point

Park,

You,

et al. 2024

2023 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2023) Proceedings

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Pose Estimation with Dual Quaternions and Iterative Closest Point

Cited by 4 publications

References 22 publications

DPO: Direct Planar Odometry with Stereo Camera

DPO: Direct Planar Odometry with Stereo Camera

Dual Quaternion Particle Filtering for Pose Estimation

Vision Based Robust Pose Estimation Using Multiplicative Extended Kalman Filter and Iterative Closest Point

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