Robust Pose Estimation With an Outlier Diagnosis Based on a Relaxation of Rigid Body Constraints

Author(s):  
Yu Lin ◽  
Xiao-wei Tu ◽  
Fengfeng Xi ◽  
Vincent Chan

In this paper, we propose a novel outlier diagnosis method for robust pose estimation of rigid body motions from outlier contaminated 3D point measurements. Due to incorrect correspondences in a cluttered measuring environment, observed point data are contaminated by outliers, which are unusual gross errors that lie out of an overall error distribution. Standard least-squares methods for pose estimation are highly sensitive to outliers. For this reason, an outlier diagnosis method is developed to preprocess measured point data prior to pose estimation. This diagnosis method detects and removes outliers based on a relaxation method with rigid body constraints of a rigid body. Simulations and experiments prove the effectiveness and advantages of high breakdown point and ease of implementation.

Robotica ◽  
2021 ◽  
pp. 1-19
Author(s):  
Timothy D. Barfoot ◽  
James R. Forbes ◽  
Gabriele M. T. D’Eleuterio

Abstract Robotics and computer vision problems commonly require handling rigid-body motions comprising translation and rotation – together referred to as pose. In some situations, a vectorial parameterization of pose can be useful, where elements of a vector space are surjectively mapped to a matrix Lie group. For example, these vectorial representations can be employed for optimization as well as uncertainty representation on groups. The most common mapping is the matrix exponential, which maps elements of a Lie algebra onto the associated Lie group. However, this choice is not unique. It has been previously shown how to characterize all such vectorial parameterizations for SO(3), the group of rotations. Some results are also known for the group of poses, where it is possible to build a family of vectorial mappings that includes the matrix exponential as well as the Cayley transformation. We extend what is known for these pose mappings to the $4 \times 4$ representation common in robotics and also demonstrate three different examples of the proposed pose mappings: (i) pose interpolation, (ii) pose servoing control, and (iii) pose estimation in a pointcloud alignment problem. In the pointcloud alignment problem, our results lead to a new algorithm based on the Cayley transformation, which we call CayPer.


1987 ◽  
Vol 15 (8) ◽  
pp. 923-944 ◽  
Author(s):  
Emmanuel A. Maragakis ◽  
Paul C. Jennings

2012 ◽  
Vol 12 (06) ◽  
pp. 1250049 ◽  
Author(s):  
A. RASTI ◽  
S. A. FAZELZADEH

In this paper, multibody dynamic modeling and flutter analysis of a flexible slender vehicle are investigated. The method is a comprehensive procedure based on the hybrid equations of motion in terms of quasi-coordinates. The equations consist of ordinary differential equations for the rigid body motions of the vehicle and partial differential equations for the elastic deformations of the flexible components of the vehicle. These equations are naturally nonlinear, but to avoid high nonlinearity of equations the elastic displacements are assumed to be small so that the equations of motion can be linearized. For the aeroelastic analysis a perturbation approach is used, by which the problem is divided into a nonlinear flight dynamics problem for quasi-rigid flight vehicle and a linear extended aeroelasticity problem for the elastic deformations and perturbations in the rigid body motions. In this manner, the trim values that are obtained from the first problem are used as an input to the second problem. The body of the vehicle is modeled with a uniform free–free beam and the aeroelastic forces are derived from the strip theory. The effect of some crucial geometric and physical parameters and the acting forces on the flutter speed and frequency of the vehicle are investigated.


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