A Novel Method for Preoperative 6D Pose Estimation of Rat Skull Based on 3D Vision Techniques

2021 ◽  
Author(s):  
Yujun Wu ◽  
Hanwei Chen ◽  
Bo Han ◽  
Chao Liu ◽  
Xinjun Sheng
Keyword(s):  
Pose Estimation ◽  
3D Vision ◽  
Novel Method

scholarly journals 6D pose estimation with combined deep learning and 3D vision techniques for a fast and accurate object grasping

2021 ◽  
pp. 103775
Author(s):  
Tuan-Tang Le ◽  
Trung-Son Le ◽  
Yu-Ru Chen ◽  
Joel Vidal ◽  
Chyi-Yeu Lin
Keyword(s):  
Deep Learning ◽  
Pose Estimation ◽  
3D Vision

scholarly journals A Coarse-to-Fine Method for Estimating the Axis Pose Based on 3D Point Clouds in Robotic Cylindrical Shaft-in-Hole Assembly

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4064
Author(s):  
Can Li ◽  
Ping Chen ◽  
Xin Xu ◽  
Xinyu Wang ◽  
Aijun Yin
Keyword(s):  
Pose Estimation ◽  
Point Clouds ◽  
Geometric Constraints ◽  
Admittance Control ◽  
3D Vision ◽  
Axis Orientation ◽  
3D Point Clouds ◽  
Object Pose Estimation ◽  
Traditional Approaches ◽  
Coarse To Fine

In this work, we propose a novel coarse-to-fine method for object pose estimation coupled with admittance control to promote robotic shaft-in-hole assembly. Considering that traditional approaches to locate the hole by force sensing are time-consuming, we employ 3D vision to estimate the axis pose of the hole. Thus, robots can locate the target hole in both position and orientation and enable the shaft to move into the hole along the axis orientation. In our method, first, the raw point cloud of a hole is processed to acquire the keypoints. Then, a coarse axis is extracted according to the geometric constraints between the surface normals and axis. Lastly, axis refinement is performed on the coarse axis to achieve higher precision. Practical experiments verified the effectiveness of the axis pose estimation. The assembly strategy composed of axis pose estimation and admittance control was effectively applied to the robotic shaft-in-hole assembly.

scholarly journals Visual Navigation for Recovering an AUV by Another AUV in Shallow Water

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1889 ◽  
Author(s):  
Shuang Liu ◽  
Hongli Xu ◽  
Yang Lin ◽  
Lei Gao
Keyword(s):  
Shallow Water ◽  
Pose Estimation ◽  
Field Experiments ◽  
State Of The Art ◽  
Autonomous Underwater Vehicles ◽  
Visual Navigation ◽  
Ambient Light ◽  
Robust Detection ◽  
Novel Method ◽  
Coarse To Fine

Autonomous underwater vehicles (AUVs) play very important roles in underwater missions. However, the reliability of the automated recovery of AUVs has still not been well addressed. We propose a vision-based framework for automatically recovering an AUV by another AUV in shallow water. The proposed framework contains a detection phase for the robust detection of underwater landmarks mounted on the docking station in shallow water and a pose-estimation phase for estimating the pose between AUVs and underwater landmarks. We propose a Laplacian-of-Gaussian-based coarse-to-fine blockwise (LCB) method for the detection of underwater landmarks to overcome ambient light and nonuniform spreading, which are the two main problems in shallow water. We propose a novel method for pose estimation in practical cases where landmarks are broken or covered by biofouling. In the experiments, we show that our proposed LCB method outperforms the state-of-the-art method in terms of remote landmark detection. We then combine our proposed vision-based framework with acoustic sensors in field experiments to demonstrate its effectiveness in the automated recovery of AUVs.

A novel method of camera pose estimation by parabolic motion

Optik ◽  
2013 ◽  
Vol 124 (24) ◽  
pp. 6840-6845 ◽  
Author(s):  
Wei Liu ◽  
Wenxiao Shi ◽  
Yaowen Lv ◽  
Jingtai Cao ◽  
Yumei Yin ◽  
...  
Keyword(s):  
Pose Estimation ◽  
Camera Pose Estimation ◽  
Camera Pose ◽  
Novel Method

Crater Edge-based Flexible Autonomous Navigation for Planetary Landing

2018 ◽  
Vol 72 (3) ◽  
pp. 649-668
Author(s):  
Yang Tian ◽  
Meng Yu ◽  
Meibao Yao ◽  
Xiangyu Huang
Keyword(s):  
Pose Estimation ◽  
Autonomous Navigation ◽  
State Of The Art ◽  
Estimation Accuracy ◽  
Illumination Direction ◽  
Crater Detection ◽  
Planetary Landing ◽  
Novel Method ◽  
Edge Based ◽  
Navigation Method

In this paper, a novel method for autonomous navigation for an extra-terrestrial body landing mission is proposed. Based on state-of-the-art crater detection and matching algorithms, a crater edge-based navigation method is formulated, in which solar illumination direction is adopted as a complementary optical cue to aid crater edge-based navigation when only one crater is available. To improve the pose estimation accuracy, a distributed Extended Kalman Filter (EKF) is developed to encapsulate the crater edge-based estimation approach. Finally, the effectiveness of proposed approach is validated by Monte Carlo simulations using a specifically designed planetary landing simulation toolbox.

Laser interferometry measurements based calibration and error propagation identification for pose estimation in mobile robots

Robotica ◽  
2013 ◽  
Vol 32 (1) ◽  
pp. 165-174 ◽  
Author(s):  
Paulo A. Jiménez ◽  
Bijan Shirinzadeh
Keyword(s):  
Mobile Robots ◽  
Pose Estimation ◽  
Error Propagation ◽  
Laser Interferometry ◽  
Error Variance ◽  
Calibration Method ◽  
Novel Method ◽  
Position And Orientation ◽  
Odometry Calibration ◽  
Two Parameter

SUMMARYA widely used method for pose estimation in mobile robots is odometry. Odometry allows the robot in real time to reconstruct its position and orientation from the wheels' encoder measurements. Given to its unbounded nature, odometry calculation accumulates errors with quadratic increase of error variance with traversed distance. This paper develops a novel method for odometry calibration and error propagation identification for mobile robots. The proposed method uses a laser-based interferometer to measure distance precisely. Two variants of the proposed calibration method are examined: the two-parameter model and the three-parameter model. Experimental results obtained using a Khepera 3 mobile robot showed that both methods significantly increase accuracy of the pose estimation, validating the effectiveness of the proposed calibration method.

scholarly journals A Novel Method for the Absolute Pose Problem with Pairwise Constraints

2019 ◽  
Vol 11 (24) ◽  
pp. 3007 ◽  
Author(s):  
Yinlong Liu ◽  
Xuechen Li ◽  
Manning Wang ◽  
Alois Knoll ◽  
Guang Chen ◽  
...  
Keyword(s):  
Pose Estimation ◽  
Optimal Algorithm ◽  
Optimization Method ◽  
Estimation Problem ◽  
Parameter Estimation Problem ◽  
Real World Data ◽  
Pairwise Constraints ◽  
Optimal Rotation ◽  
Novel Method ◽  
The Absolute

Absolute pose estimation from corrupted point correspondences is typically a problem of estimating parameters from outlier-contaminated data. Conventionally, for a fixed dimensionality d and the number of measurements N, a robust estimation problem cannot be solved exactly faster than O ( N d ) . Furthermore, it is almost impossible to remove d from the exponent of the runtime of a globally optimal algorithm. However, absolute pose estimation is a geometric parameter estimation problem, and thus has special constraints. In this paper, we consider pairwise constraints and propose a novel algorithm utilizing global optimization method Branch-and-Bound (BnB) for solving the absolute pose estimation problem. Concretely, we first decouple the rotation and the translation subproblems by utilizing the pairwise constraints, and then we solve the rotation subproblem using the BnB algorithm. Lastly, we estimate the translation based on the optimal rotation by using another BnB algorithm. The proposed algorithm has an approximately linear complexity in the number of correspondences at a given outlier ratio. The advantages of our method were demonstrated via thorough testing on both synthetic and real-world data.

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