scholarly journals Pose Estimation of Uncooperative Unknown Space Objects from a Single Image

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Xiaoyuan Ren ◽  
Libing Jiang ◽  
Zhuang Wang
Keyword(s):  
Pose Estimation ◽  
Experimental Results ◽  
Single Image ◽  
Space Object ◽  
Shape Model ◽  
Structure Information ◽  
Space Objects ◽  
Specific Object ◽  
Unknown Objects ◽  
Unknown Object

Estimating the 3D pose of the space object from a single image is an important but challenging work. Most of the existing methods estimate the 3D pose of known space objects and assume that the detailed geometry of a specific object is known. These methods are not available for unknown objects without the known geometry of the object. In contrast to previous works, this paper devotes to estimate the 3D pose of the unknown space object from a single image. Our method estimates not only the pose but also the shape of the unknown object from a single image. In this paper, a hierarchical shape model is proposed to represent the prior structure information of typical space objects. On this basis, the parameters of the pose and shape are estimated simultaneously for unknown space objects. Experimental results demonstrate the effectiveness of our method to estimate the 3D pose and infer the geometry of unknown typical space objects from a single image. Moreover, experimental results show the advantage of our approach over the methods relying on the known geometry of the object.

METHOD FOR ESTIMATING PARAMETERS OF GENERALIZED MODEL OF LUMINOSITY OF SPACE OBJECTS BASED ON DATA FROM DIFFERENT RANGES

2018 ◽  
pp. 57-62
Author(s):  
E. I. Gundrova ◽  
A. P. Lukyanov ◽  
A. V. Pruglo ◽  
S. S. Ravdin
Keyword(s):  
Phase Angle ◽  
Real Data ◽  
Model Data ◽  
Space Object ◽  
Distribution Law ◽  
Generalized Model ◽  
Measurement Results ◽  
Space Objects ◽  
Reference Distance

Previously, the authors have proposed a generalized model for estimating the distribution law parameters of luminosity of space objects, assuming that not only successful but also unsuccessful measurement results are taken into account. Estimation was done on the data of observations under similar conditions: phase angle, range, sensibility of the telescope. The algorithm under such limitations was tested on model data and real measurements. Therefore, obtained results showed that algorithm did not fit for cases of changing range of space objects. In this work, the new algorithm, that allows to merge information from different ranges to the observed space object, is proposed. In this case, luminosity values are reduced to the ones at a reference distance of 1000 km considering sensibility of the telescope. To obtain estimates of the parameters the Cramer-Mises-Smirnov criterion is used. This algorithm was tested on model data and results of its work on real data were obtained. The data showed correct work of the algorithm and also confirmed the practicability of organization the registration of unsuccessful measurements.

Estimated path information gain-based robot exploration under perceptual uncertainty

Robotica ◽  
2022 ◽  
pp. 1-17
Author(s):  
Jie Liu ◽  
Chaoqun Wang ◽  
Wenzheng Chi ◽  
Guodong Chen ◽  
Lining Sun
Keyword(s):  
Decision Making ◽  
Topological Structure ◽  
Information Gain ◽  
State Of The Art ◽  
Selection Process ◽  
Random Trees ◽  
Experimental Results ◽  
Restricted Area ◽  
Structure Information ◽  
Path Information

Abstract At present, the frontier-based exploration has been one of the mainstream methods in autonomous robot exploration. Among the frontier-based algorithms, the method of searching frontiers based on rapidly exploring random trees consumes less computing resources with higher efficiency and performs well in full-perceptual scenarios. However, in the partially perceptual cases, namely when the environmental structure is beyond the perception range of robot sensors, the robot often lingers in a restricted area, and the exploration efficiency is reduced. In this article, we propose a decision-making method for robot exploration by integrating the estimated path information gain and the frontier information. The proposed method includes the topological structure information of the environment on the path to the candidate frontier in the frontier selection process, guiding the robot to select a frontier with rich environmental information to reduce perceptual uncertainty. Experiments are carried out in different environments with the state-of-the-art RRT-exploration method as a reference. Experimental results show that with the proposed strategy, the efficiency of robot exploration has been improved obviously.

scholarly journals Simulation and automation of aluminium panel shot peen forming

2022 ◽  
Author(s):  
Vladislav Sushitskii ◽  
Pierre-Olivier Dubois ◽  
Hong Yan Miao ◽  
Martin levesque ◽  
Frederick Gosselin
Keyword(s):  
Shot Peening ◽  
Pattern Generation ◽  
Experimental Results ◽  
Shape Model ◽  
Peen Forming ◽  
Metal Plates ◽  
Airplane Wing ◽  
Aluminum Plates ◽  
Doubly Curved

We present a methodology for automated forming of metal plates into freeformshapes using shot peening. The methodology is based on a simulation softwarethat computes the peening pattern and simulates the effect of its application.The pattern generation requires preliminary experimental characterizationof the treatment. The treatment is applied by a shot peening robot. The program for the robot is generated automatically according to the peening pattern. We validate the methodology with a series of tests. Namely, we form nine aluminum plates into doubly curved shapes and we also shape model airplane wing skins. The article describes the complete workflow and the experimental results.

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