Modification of geocentric distance error of space camera

2012 ◽  
Vol 20 (5) ◽  
pp. 1126-1133
Author(s):  
李伟雄 LI Wei-xiong ◽  
闫得杰 YAN De-jie ◽  
徐抒岩 XU Shu-yan ◽  
胡君 Hu Jun
Keyword(s):  
Distance Error ◽  
Geocentric Distance

Kinematic Calibration Method of Robots Based on Distance Error

ROBOT ◽  
2013 ◽  
Vol 35 (5) ◽  
pp. 600 ◽  
Author(s):  
Wenbin GAO ◽  
Hongguang WANG ◽  
Yong JIANG ◽  
Xin'an PAN
Keyword(s):  
Calibration Method ◽  
Kinematic Calibration ◽  
Distance Error

scholarly journals Noise power spectral density scaled SNR response estimation with restricted range search for sound source localisation using unmanned aerial vehicles

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Benjamin Yen ◽  
Yusuke Hioka
Keyword(s):  
Spectral Density ◽  
Noise Reduction ◽  
Power Spectral Density ◽  
Sound Source ◽  
Processing Algorithm ◽  
Post Processing ◽  
Time Frequency ◽  
Distance Error ◽  
Rotor Noise ◽  
Power Spectral

Abstract A method to locate sound sources using an audio recording system mounted on an unmanned aerial vehicle (UAV) is proposed. The method introduces extension algorithms to apply on top of a baseline approach, which performs localisation by estimating the peak signal-to-noise ratio (SNR) response in the time-frequency and angular spectra with the time difference of arrival information. The proposed extensions include a noise reduction and a post-processing algorithm to address the challenges in a UAV setting. The noise reduction algorithm reduces influences of UAV rotor noise on localisation performance, by scaling the SNR response using power spectral density of the UAV rotor noise, estimated using a denoising autoencoder. For the source tracking problem, an angular spectral range restricted peak search and link post-processing algorithm is also proposed to filter out incorrect location estimates along the localisation path. Experimental results show the proposed extensions yielded improvements in locating the target sound source correctly, with a 0.0064–0.175 decrease in mean haversine distance error across various UAV operating scenarios. The proposed method also shows a reduction in unexpected location estimations, with a 0.0037–0.185 decrease in the 0.75 quartile haversine distance error.

Elliptical Orbit of Asteroid 1986 QE1

1989 ◽  
Vol 12 ◽  
pp. 21-24
Author(s):  
H. Debehogne ◽  
L.E. Machado ◽  
S. Vaz ◽  
E.R. Netto
Keyword(s):  
Photographic Plate ◽  
Elliptical Orbit ◽  
Orbital Elements ◽  
European Southern Observatory ◽  
Geocentric Distance ◽  
Before And After

We present the orbital elements of asteroid QE1 (pro visional designation) identified in august 26, 1986, on a photographic plate obtained at the GPO telescope of the European Southern Observatory (ESO), La Silla, Chile, as well as the positions (AR and Dec) referred to 1950.0. Residues (0 - C) of the position in AR and Dec of the asteroid are given, both before and after applying variation in the geocentric distance.

scholarly journals The Cognition of Maximal Reach Distance in Parkinson’s Disease

2016 ◽  
Vol 2016 ◽  
pp. 1-8
Author(s):  
Satoru Otsuki ◽  
Masanori Nagaoka
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Rating Scale ◽  
Target Object ◽  
Clinical Findings ◽  
Reaching Movements ◽  
Spatial Distance ◽  
Distance Error ◽  
Healthy Elderly ◽  
Disease Rating

This study aimed to investigate whether the cognition of spatial distance in reaching movements was decreased in patients with Parkinson’s disease (PD) and whether this cognition was associated with various symptoms of PD. Estimated and actual maximal reaching distances were measured in three directions in PD patients and healthy elderly volunteers. Differences between estimated and actual measurements were compared within each group. In the PD patients, the associations between “error in cognition” of reaching distance and “clinical findings” were also examined. The results showed that no differences were observed in any values regardless of dominance of hand and severity of symptoms. The differences between the estimated and actual measurements were negatively deviated in the PD patients, indicating that they tended to underestimate reaching distance. “Error in cognition” of reaching distance correlated with the items of posture in the motor section of the Unified Parkinson’s Disease Rating Scale. This suggests that, in PD patients, postural deviation and postural instability might affect the cognition of the distance from a target object.

scholarly journals Minimal medical imaging can accurately reconstruct geometric bone models for musculoskeletal models

2018 ◽  
Author(s):  
Edin K. Suwarganda ◽  
Laura E. Diamond ◽  
David J. Saxby ◽  
David G. Lloyd ◽  
A. Killen Bryce ◽  
...  
Keyword(s):  
Motion Capture ◽  
Linear Scaling ◽  
Bone Segmentation ◽  
Shape Modelling ◽  
Distance Error ◽  
Musculoskeletal Models ◽  
Subject Specific ◽  
Statistical Shape ◽  
Statistical Shape Modelling ◽  
Complete Sets

AbstractAccurate representation of subject-specific bone anatomy in lower-limb musculoskeletal models is important for human movement analyses and simulations. Mathematical methods can reconstruct geometric bone models using incomplete imaging of bone by morphing bone model templates, but the validity of these methods has not been fully explored. The purpose of this study was to determine the minimal imaging requirements for accurate reconstruction of geometric bone models. Complete geometric pelvis and femur models of 14 healthy adults were reconstructed from magnetic resonance imaging through segmentation. From each complete bone segmentation, three sets of incomplete segmentations (set 1 being the most incomplete) were created to test the effect of imaging incompleteness on reconstruction accuracy. Geometric bone models were reconstructed from complete sets, three incomplete sets, and two motion capture-based methods. Reconstructions from (in)complete sets were generated using statistical shape modelling, followed by host-mesh and local-mesh fitting through the Musculoskeletal Atlas Project Client. Reconstructions from motion capture-based methods used positional data from skin surface markers placed atop anatomic landmarks and estimated joint centre locations as target points for statistical shape modelling and linear scaling. Accuracy was evaluated with distance error (mm) and overlapping volume similarity (%) between complete bone segmentation and reconstructed bone models, and statistically compared using a repeated measure analysis of variance (p<0.05). Motion capture-based methods produced significantly higher distance error than reconstructions from (in)complete sets. Pelvis volume similarity reduced significantly with the level of incompleteness: complete set (92.70±1.92%), set 3 (85.41±1.99%), set 2 (81.22±3.03%), set 1 (62.30±6.17%), motion capture-based statistical shape modelling (41.18±9.54%), and motion capture-based linear scaling (26.80±7.19%). A similar trend was observed for femur volume similarity. Results indicate that imaging two relevant bone regions produces overlapping volume similarity > 80% compared to complete segmented bone models. These findings have implications for improving movement analysis and simulation with subject-specific musculoskeletal models.

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