scholarly journals Machine-Vision-Based Pose Estimation System Using Sensor Fusion for Autonomous Satellite Grappling

2013 ◽  
Author(s):  
Andres Felipe Velasquez Escandon
Keyword(s):  
Machine Vision ◽  
Sensor Fusion ◽  
Pose Estimation ◽  
Estimation System

Addressing pose estimation issues for machine vision based UAV autonomous serial refuelling

2007 ◽  
Vol 111 (1120) ◽  
pp. 389-396 ◽  
Author(s):  
G. Campa ◽  
M. R. Napolitano ◽  
M. Perhinschi ◽  
M. L. Fravolini ◽  
L. Pollini ◽  
...  
Keyword(s):  
Machine Vision ◽  
Pose Estimation ◽  
Estimation Algorithm ◽  
Computational Effort ◽  
Unmanned Aircraft ◽  
Light Sources ◽  
Estimation Algorithms ◽  
Trade Offs ◽  
Labeling Algorithms ◽  
Selection Of

Abstract This paper describes the results of an effort on the analysis of the performance of specific ‘pose estimation’ algorithms within a Machine Vision-based approach for the problem of aerial refuelling for unmanned aerial vehicles. The approach assumes the availability of a camera on the unmanned aircraft for acquiring images of the refuelling tanker; also, it assumes that a number of active or passive light sources – the ‘markers’ – are installed at specific known locations on the tanker. A sequence of machine vision algorithms on the on-board computer of the unmanned aircraft is tasked with the processing of the images of the tanker. Specifically, detection and labeling algorithms are used to detect and identify the markers and a ‘pose estimation’ algorithm is used to estimate the relative position and orientation between the two aircraft. Detailed closed-loop simulation studies have been performed to compare the performance of two ‘pose estimation’ algorithms within a simulation environment that was specifically developed for the study of aerial refuelling problems. Special emphasis is placed on the analysis of the required computational effort as well as on the accuracy and the error propagation characteristics of the two methods. The general trade offs involved in the selection of the pose estimation algorithm are discussed. Finally, simulation results are presented and analysed.

Vehicle Pose Estimation System Base on Pressure Sensor Array for Clamping Parking Robot

2021 ◽  
Author(s):  
Juzhong Zhang ◽  
Yuyi Chu ◽  
Zhisen Wang ◽  
Tingfeng Ye ◽  
Liming Cai ◽  
...  
Keyword(s):  
Pose Estimation ◽  
Pressure Sensor ◽  
Sensor Array ◽  
Estimation System

scholarly journals IMAGE-BASED ORIENTATION DETERMINATION OF MOBILE SENSOR PLATFORMS

2021 ◽  
Vol XLIII-B1-2021 ◽  
pp. 215-220
Author(s):  
O. Hasler ◽  
S. Nebiker
Keyword(s):  
Sensor Fusion ◽  
Pose Estimation ◽  
Reference System ◽  
Laser Scanner ◽  
Relative Orientation ◽  
Robotic Platform ◽  
Sensor Platforms ◽  
Local Reference ◽  
The Absolute ◽  
Additional Approach

Abstract. Estimating the pose of a mobile robotic platform is a challenging task, especially when the pose needs to be estimated in a global or local reference frame and when the estimation has to be performed while the platform is moving. While the position of a platform can be measured directly via modern tachymetry or with the help of a global positioning service GNSS, the absolute platform orientation is harder to derive. Most often, only the relative orientation is estimated with the help of a sensor mounted on the robotic platform such as an IMU, with one or multiple cameras, with a laser scanner or with a combination of any of those. Then, a sensor fusion of the relative orientation and the absolute position is performed. In this work, an additional approach is presented: first, an image-based relative pose estimation with frames from a panoramic camera using a state-of-the-art visual odometry implementation is performed. Secondly, the position of the platform in a reference system is estimated using motorized tachymetry. Lastly, the absolute orientation is calculated using a visual marker, which is placed in the space, where the robotic platform is moving. The marker can be detected in the camera frame and since the position of this marker is known in the reference system, the absolute pose can be estimated. To improve the absolute pose estimation, a sensor fusion is conducted. Results with a Lego model train as a mobile platform show, that the trajectory of the absolute pose calculated independently with four different markers have a deviation < 0.66 degrees 50% of the time and that the average difference is < 1.17 degrees. The implementation is based on the popular Robotic Operating System ROS.

Sign in / Sign up

Export Citation Format

Share Document