scholarly journals Landing site positioning and descent trajectory reconstruction of Tianwen-1 on Mars

Astrodynamics ◽  
2022 ◽  
Vol 6 (1) ◽  
pp. 69-79
Author(s):  
Anran Wang ◽  
Li Wang ◽  
Yinuo Zhang ◽  
Baocheng Hua ◽  
Tao Li ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
Feature Matching ◽  
Mean Squared Error ◽  
Landing Site ◽  
Positional Accuracy ◽  
Geometric Transformations ◽  
Descent Trajectory ◽  
Digital Orthophoto ◽  
Interplanetary Mission

AbstractTianwen-1 (TW-1) is the first Chinese interplanetary mission to have accomplished orbiting, landing, and patrolling in a single exploration of Mars. After safe landing, it is essential to reconstruct the descent trajectory and determine the landing site of the lander. For this purpose, we processed descent images of the TW-1 optical obstacle-avoidance sensor (OOAS) and digital orthophoto map (DOM) of the landing area using our proposed hybrid-matching method, in which the landing process is divided into two parts. In the first, crater matching is used to obtain the geometric transformations between the OOAS images and DOM to calculate the position of the lander. In the second, feature matching is applied to compute the position of the lander. We calculated the landing site of TW-1 to be 109.9259° E, 25.0659° N with a positional accuracy of 1.56 m and reconstructed the landing trajectory with a horizontal root mean squared error of 1.79 m. These results will facilitate the analyses of the obstacle-avoidance system and optimize the control strategy in the follow-up planetary-exploration missions.

Shadow–highlight feature matching automatic small crater recognition using high-resolution digital orthophoto map from Chang’E Missions

2019 ◽  
Vol 38 (4) ◽  
pp. 541-554
Author(s):  
Wei Zuo ◽  
Chunlai Li ◽  
Lingjie Yu ◽  
Zhoubin Zhang ◽  
Rongwu Wang ◽  
...  
Keyword(s):  
High Resolution ◽  
Feature Matching ◽  
Small Crater ◽  
Digital Orthophoto

scholarly journals Obstacle Avoidance Model for UAVs with Joint Target based on Multi-Strategies and Follow-up Vector Field

2020 ◽  
Vol 170 ◽  
pp. 257-264 ◽  
Author(s):  
Xue Zheng ◽  
Stéphane Galland ◽  
Xiaowei Tu ◽  
Qinghua Yang ◽  
Alexandre Lombard ◽  
...  
Keyword(s):  
Vector Field ◽  
Obstacle Avoidance

scholarly journals Predicting GPA at Age 15 in the Fragile Families and Child Wellbeing Study

2019 ◽  
Vol 5 ◽  
pp. 237802311882480 ◽  
Author(s):  
Louis Raes
Keyword(s):  
Mean Squared Error ◽  
Fragile Families ◽  
Child Wellbeing ◽  
Teacher Observations ◽  
Squared Error ◽  
Predicting Gpa

In this paper, we describe in detail the different approaches we used to predict the GPA of children at the age of 15 in the context of the Fragile Families Challenge. Our best prediction improved about 18 percent in terms of mean squared error over a naive baseline prediction and performed less than 5 percent worse than the best prediction in the Fragile Families Challenge. After discussing the different predictions we made, we also discuss the predictors that tend to be robustly associated with GPA. One remarkable predictor is related to teacher observations at the age of nine. We end with a reflection on our participation in the Fragile Families Challenge and provide some suggestions for follow-up work.

ON IMPROVEMENT OF PARACHUTE-RETROROCKET AIRDROP SYSTEM

2019 ◽  
pp. 5-13
Author(s):  
Yu. Adamov ◽  
K. Boriak ◽  
V. Zavalniuk
Keyword(s):  
Horizontal Plane ◽  
Slope Angle ◽  
Ground Surface ◽  
Landing Site ◽  
Earth Surface ◽  
Jet Engines ◽  
The Earth ◽  
Descent Trajectory ◽  
The Absolute ◽  
Absolute Altitude

The paper is devoted to the study of the prospects for improving the parachute-retrorocket airdrop system (PRS) in order to increase its reliability and enable the ability to adjust the orientation of a load in the horizontal plane depending on the slope of the earth's surface at the landing site. The primary task is to improve the accuracy of the altimeter, which determines the triggering moment of the PRS jet engines. The replacement of a mechanical altimeter of an outdated design with a modern electronic radio altimeter based on phased array radar is proposed, which allows to improve the accuracy of determining the absolute altitude(distance to the ground) and to take into account a roll of the load during the descent. The ways of determining the slope of earth's surface at the estimated landing site are also discussed. The results obtained make it possible to increase the accuracy of radio altimeter operation and significantly reduce the probability of an error in determining the absolute altitude due to rocking or static roll of the object. In addition to determining the current values of the height and speed of the descent of the vehicle, the use of a scanning radar makes it possible to estimate the inclination angle of the Earth’s surface at the landing site (in the radar scanning plane). If a certain angle of inclination of the earth surface at the landing site turns out to be too large, the probability of a successful landing can be increased by correcting the object's descent path, taking into account the information received. One of the easiest ways to correct a descent trajectory is to equip an object with small aerodynamic elements (rudders) and electromechanical actuators, ensuring their necessary orientation based on the results of determining the surface relief with radar. As one of the options, the authors propose the use of additional jet engines, which are structurally located on opposite sides of the object of landing in such a way as to form a torque of rotation of the object in a space from 0 ° to 90 ° in the horizontal plane due to the kinetic energy of motion from the actuation of jet engines. The triggering moment of the squibs is calculated based on determining the optimal distance of the object to the ground surface, and the need for triggering the squibs to rotate the object (correcting its position in space) depends on a certain value of the slope angle of the earth surface and comparing it with the admissible critical values of the angle, at which the object loses its stability during landing.

scholarly journals Using negative-latency gravitational wave alerts to detect prompt radio bursts from binary neutron star mergers with the Murchison Widefield Array

2019 ◽  
Vol 489 (1) ◽  
pp. L75-L79 ◽  
Author(s):  
Clancy W James ◽  
Gemma E Anderson ◽  
Linqing Wen ◽  
Joel Bosveld ◽  
Qi Chu ◽  
...  
Keyword(s):  
Neutron Star ◽  
Gravitational Wave ◽  
Radio Signal ◽  
Low Frequency ◽  
Positional Accuracy ◽  
Binary Neutron Star ◽  
Observational Mode ◽  
Fast Radio Burst ◽  
Murchison Widefield Array

ABSTRACT We examine how fast radio burst (FRB)-like signals predicted to be generated during the merger of a binary neutron star (BNS) may be detected in low-frequency radio observations triggered by the aLIGO/Virgo gravitational-wave detectors. The rapidity, directional accuracy, and sensitivity of follow-up observations with the Murchison Widefield Array (MWA) are considered. We show that with current methodology, the rapidity criterion fails for triggered MWA observations above 136 MHz for BNS mergers within the aLIGO/Virgo horizon, for which little dispersive delay is expected. A calculation of the expected reduction in response time by triggering on ‘negative latency’ alerts from aLIGO/Virgo observations of gravitational waves generated by the BNS inspiral is presented. This allows for observations up to 300 MHz where the radio signal is expected to be stronger. To compensate for the poor positional accuracy expected from these alerts, we propose a new MWA observational mode that is capable of viewing one-quarter of the sky. We show the sensitivity of this mode is sufficient to detect an FRB-like burst from an event similar to GW 170817 if it occurred during the ongoing aLIGO/Virgo third science run (O3).

Robust ground plane region detection using multiple visual cues for obstacle avoidance of a mobile robot

Robotica ◽  
2014 ◽  
Vol 33 (2) ◽  
pp. 436-450 ◽  
Author(s):  
Chia-How Lin ◽  
Kai-Tai Song
Keyword(s):  
Image Processing ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Visual Cues ◽  
Feature Matching ◽  
Imaging System ◽  
Ground Plane ◽  
Image Plane ◽  
Monocular Camera ◽  
Camera View

SUMMARYThis paper presents a vision-based obstacle avoidance design using a monocular camera onboard a mobile robot. A novel image processing procedure is developed to estimate the distance between the robot and obstacles based-on inverse perspective transformation (IPT) in an image plane. A robust image processing solution is proposed to detect and segment a drivable ground area within the camera view. The proposed method integrates robust feature matching with adaptive color segmentation for plane estimation and tracking to cope with variations in illumination and camera view. After IPT and ground region segmentation, distance measurement results are obtained similar to those of a laser range finder for mobile robot obstacle avoidance and navigation. The merit of this algorithm is that the mobile robot can have the capacity of path finding and obstacle avoidance by using a single monocular camera. Practical experimental results on a wheeled mobile robot show that the proposed imaging system successfully obtains distances of surrounding objects for reactive navigation in an indoor environment.

scholarly journals Semi-Supervised Deep Learning for Lunar Crater Detection Using CE-2 DOM

2021 ◽  
Vol 13 (14) ◽  
pp. 2819
Author(s):  
Sudong Zang ◽  
Lingli Mu ◽  
Lina Xian ◽  
Wei Zhang
Keyword(s):  
Deep Learning ◽  
Landing Site ◽  
Training Data ◽  
The Moon ◽  
Detection Model ◽  
Processing Times ◽  
Crater Detection ◽  
High Resolution Imagery ◽  
Model Training ◽  
Digital Orthophoto

Lunar craters are very important for estimating the geological age of the Moon, studying the evolution of the Moon, and for landing site selection. Due to a lack of labeled samples, processing times due to high-resolution imagery, the small number of suitable detection models, and the influence of solar illumination, Crater Detection Algorithms (CDAs) based on Digital Orthophoto Maps (DOMs) have not yet been well-developed. In this paper, a large number of training data are labeled manually in the Highland and Maria regions, using the Chang’E-2 (CE-2) DOM; however, the labeled data cannot cover all kinds of crater types. To solve the problem of small crater detection, a new crater detection model (Crater R-CNN) is proposed, which can effectively extract the spatial and semantic information of craters from DOM data. As incomplete labeled samples are not conducive for model training, the Two-Teachers Self-training with Noise (TTSN) method is used to train the Crater R-CNN model, thus constructing a new model—called Crater R-CNN with TTSN—which can achieve state-of-the-art performance. To evaluate the accuracy of the model, three other detection models (Mask R-CNN, no-Mask R-CNN, and Crater R-CNN) based on semi-supervised deep learning were used to detect craters in the Highland and Maria regions. The results indicate that Crater R-CNN with TTSN achieved the highest precision (of 91.4% and 88.5%, respectively) in the Highland and Maria regions, even obtaining the highest recall and F1 score. Compared with Mask R-CNN, no-Mask R-CNN, and Crater R-CNN, Crater R-CNN with TTSN had strong robustness and better generalization ability for crater detection within 1 km in different terrains, making it possible to detect small craters with high accuracy when using DOM data.

scholarly journals DESCENT TRAJECTORY RECOVERY OF CHANG’E-4 LANDER BASED ON DESCENT IMAGES

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1457-1461
Author(s):  
W. Wan ◽  
Z. Liu ◽  
B. Liu ◽  
K. Di ◽  
J. Wang ◽  
...  
Keyword(s):  
Least Squares ◽  
Lunar Surface ◽  
Processing Method ◽  
Bundle Adjustment ◽  
Calibration Model ◽  
South Pole ◽  
Descent Trajectory ◽  
Precision Estimation ◽  
Geometric Processing ◽  
Digital Orthophoto

<p><strong>Abstract.</strong> Chang’e-4 lander, carrying Yutu-2 rover, was successfully landed on the far side of lunar surface in Von Kármán crater inside the South Pole-Aitken basin on January 3rd, 2019. The descent images, captured by the descent camera mounted on the lander, captured the sequential descent images and recorded the scene changes during the entry, descent and landing (EDL) process. This paper proposed a bundle adjustment based geometric processing method for descent and landing trajectory recovery using descent images. A frame camera based self-calibration model was introduced for high precision estimation of interior and exterior parameters of descent images simultaneously in a least squares manners. Evenly distributed GCPs were selected from the landing area in a digital orthophoto map generated from LROC NAC images and SLDEM2015. The experimental results demonstrated the effectiveness of the proposed method in Chang’e-4 descent trajectory recovery.</p>

scholarly journals Controlling the Statistics of Action: Obstacle Avoidance

2002 ◽  
Vol 87 (5) ◽  
pp. 2434-2440 ◽  
Author(s):  
Antonia F. de C. Hamilton ◽  
Daniel M. Wolpert
Keyword(s):  
Obstacle Avoidance ◽  
Optimal Trajectory ◽  
General Framework ◽  
Mean Squared Error ◽  
Motor Command ◽  
Squared Error ◽  
Optimal Paths ◽  
Probability Of Collision ◽  
The Mean

Task optimization in the presence of signal-dependent noise (TOPS) has been proposed as a general framework for planning goal-directed movements. Within this framework, the motor command is assumed to be corrupted by signal-dependent noise, which leads to a distribution of possible movements. A task can then be equated with optimizing some function of the statistics of this distribution. We found the optimal trajectory for obstacle avoidance by minimizing the mean-squared error at the end of the movement while keeping the probability of collision with the obstacle below a fixed limit. The optimal paths accurately predicted the empirical trajectories. This demonstrates that controlling the statistics of movements in the presence of signal-dependent noise may be a fundamental and unifying principle of goal-directed movements.

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