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1 |
Design of robot automatic navigation under computer intelligent algorithm and machine vision
طراحی ربات ناوبری خودکار تحت الگوریتم هوشمند کامپیوتر و بینایی ماشین-2022 This work aims to explore the robot automatic navigation model under computer intelligent algorithms and
machine vision, so that mobile robots can better serve all walks of life. In view of the current situation of high
cost and poor work flexibility of intelligent robots, this work innovatively researches and improves the image
processing algorithm and control algorithm. In the navigation line edge detection stage, aiming at the low ef-
ficiency of the traditional ant colony algorithm, the Canny algorithm is combined to improve it, and a Canny-
based ant colony algorithm is proposed to detect the trajectory edge. In addition, the Single Shot MultiBox
Detector (SSD) algorithm is adopted to detect obstacles in the navigation trajectory of the robot. The perfor-
mance is analyzed through simulation. The results show that the navigation accuracy of the Canny-based ant
colony algorithm proposed in this work is basically stable at 89.62%, and its running time is the shortest. Further
analysis of the proposed SSD neural network through comparison with other neural networks suggests that its
feature recognition accuracy reaches 92.90%. The accuracy is at least 3.74% higher versus other neural network
algorithms, the running time is stable at about 37.99 s, and the packet loss rate is close to 0. Therefore, the
constructed mobile robot automatic navigation model can achieve high recognition accuracy under the premise
of ensuring error. Moreover, the data transmission effect is ideal. It can provide experimental basis for the later
promotion and adoption of mobile robots in various fields. keywords: الگوریتم هوش کامپیوتری | بینایی ماشین | ربات | ناوبری خودکار | الگوریتم کلونی مورچه ها | Computer intelligence algorithm | Machine vision | Robot | Automatic navigation | Ant colony algorithm |
مقاله انگلیسی |
2 |
Spacecraft relative navigation with an omnidirectional vision sensor
ناوبری نسبی سفینه فضایی با سنسور دید همه جانبه-2021 With the onset of autonomous spacecraft formation flying missions, the ability of satellites to autonomously navigate relatively to other space objects has become essential. To implement spacecraft relative navigation, relative measurements should be taken, and processed using relative state estimation. An efficient way to generate such information is by using vision-based measurements. Cameras are passive, low-energy, and information-rich sensors that do not actively interact with other space objects. However, pointing cameras with a conventional field-of-view to other space objects requires much a-priori initialization data; in particular, dedicated attitude maneuvers are needed, which may interfere with the satellite’s main mission. One way to overcome these difficulties is to use an omnidirectional vision sensor, which has a 360-degree horizontal field of view. In this work, we present the development of an omnidirectional vision sensor for satellites, which can be used for spacecraft relative navigation, formation flying, and space situational awareness. The study includes the development of the measurement equations, dynamical models, and state estimation algorithms, as well as a numerical study, an experimental investigation, and a space scalability analysis. Keywords: Omnidirectional vision sensor | Space navigation | Extended Kalman Filter | Computer vision | Spacecraft relative dynamics | Unified projection model |
مقاله انگلیسی |
3 |
Finding the shortest path in a familiar environment: A comparison between describing and walking a path after accounting for the role of individual factors
پیدا کردن کوتاه ترین مسیر در یک محیط آشنا: مقایسه بین توصیف و پیاده روی مسیر پس از حسابداری برای نقش عوامل فردی-2021 Finding the shortest path to a destination is a refined navigation ability little explored as yet in familiar envi-
ronments. The present study examined this ability when walking or describing the path, and how performance
relates to individual differences. Sixty-seven undergraduates familiar with the area around their campus were
asked to find the shortest path to a destination by walking there or describing it in writing. Several visuospatial
tasks and questionnaires were administered. It emerged that shortest path finding performance was supported by
familiarity and sense of direction. After accounting for these individual factors, participants performed better
when walking than when describing a path. Overall, the results showed that retrieving spatial knowledge about
familiar environments relates to individual differences and recall condition, walking a path being easier than
describing it. keywords: محیط زیست آشنا | کوتاه ترین مسیر پیدا کردن | شرح فضایی | توانایی واسطه | حس جهت | جهت یابی | Familiar environment | Shortest path finding | Spatial description | Visuospatial ability | Sense of direction | Navigation |
مقاله انگلیسی |
4 |
Development of a vision system for safe and high-precision soft landing on the Moon
توسعه یک سیستم بینایی برای فرود نرم و ایمن و با دقت بالا بر روی ماه-2021 Modern stage of space exploration is tightly related with the Moon research, with the deployment of long-term research stations on its surface. One of the critical elements here is a system for providing a highly accurate and reliable soft landing. The task of soft landing was solved many years ago, however, its accuracy is insufficient for modern lunar projects. Modern computer vision systems allow getting high-quality surface images at all stages of landing, and processing them in real time. The use of technical vision is beneficial due to the low weight, dimensions and energy consumption.The following tasks are assigned to the vision system: self-position determination of the landing unit and selection of a suitable place for a safe landing. Self-position determination by the video is necessary for INS data correction. Two methods are considered: detection and comparison of craters, and GHT. Both methods use the vector map and don’t require actual high- precision orthoplan. The safe site choosing method uses the found position for binding it to the desired and undesirable sites map. After that a precise choice follows, which takes into account the surface angle, smoothness, presence of extensive shadow areas. The algorithm is able to select landing sites close to those manually selected by the operator. The obtained algorithms can work in real time with the influence of interfering factors (noise, changes in the Sun position, changing of camera angle), and can be used to solve the problem.© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the 14th International Symposium “Intelligent Systems”. Keywords: Visual navigation | safe landing | landing site selection | hough transform | computer vision |
مقاله انگلیسی |
5 |
Optimal guidance laws with prescribed degree of stability
قوانین راهنمایی بهینه با درجه ثبات تعیین شده-2020 The prescribed degree of stability criterion is used. This quadratic criterion involves an increasing exponential time dependent term in the integral part of the criterion. This criterion is used for derivation of guidance laws. The derived guidance law has the classical structure of guidance gain times the zero-effort miss. The important issue is the fact that initially the guidance gain and thus the commanded acceleration are larger than in the conventional Proportional Navigation guidance law, but near the end, the commanded acceleration is smaller. The new guidance law attempts to close the zero effort miss earlier in the scenario than the conventional guidance law. Keywords: Guidance | Zero-effort-miss | Quadratic criterion | Proportional navigation |
مقاله انگلیسی |
6 |
AIS Data-Based for Statistics and Analysis of Maritime Traffic Dangerous Features: A Case Study of San Diego Costal Water
AIS مبتنی بر داده ها برای آمار و تجزیه و تحلیل ویژگی های خطرناک ترافیک دریایی: مطالعه موردی آب پایدار سن دیگو-2020 For analyzing the distribution characteristics of maritime traffic dangers and ensure the safety of ships
navigating at sea, plotting the ship’s trajectory and making statistic based on the relevant dynamic data that can be
extracted and analyzed from the Automatic Indentification System (AIS) information, the Distance to Closet Point of
Approach (DCPA) between any two ships have been computed and applied. Through constructing the innovative
three-dimensional bubbles chart to reflect the spatial characteristics from the DCPA matrix. Utilizing the Kernel
Density Estimation (KDE) method, draws the heat map in the vicinity of San Diego sea area, measures the traffic
danger characteristics of the costal sea area, and compares the analysis results with ArcGIS Pro 2.3. It reflects that the
analysis results are consistent with the actual situation. The heat map has the powerful scientificity and practicability,
can accurately measure the traffic distribution in the sea area, and provides auxiliary references for the planning and
design of the ships routing system and maritime traffic safety management. Key Words: Maritime Navigational Safety | Ship Automatic Identification System | Kernel Density Estimation | Distance to Closet Point of Approach |
مقاله انگلیسی |
7 |
Adaptive guidance and integrated navigation with reinforcement meta-learning
راهنمای تطبیقی و ناوبری یکپارچه با تقویت فرا یادگیری -2020 This paper proposes a novel adaptive guidance system developed using reinforcement meta-learning with a
recurrent policy and value function approximator. The use of recurrent network layers allows the deployed
policy to adapt in real time to environmental forces acting on the agent. We compare the performance of the DR/
DV guidance law, an RL agent with a non-recurrent policy, and an RL agent with a recurrent policy in four
challenging environments with unknown but highly variable dynamics. These tasks include a safe Mars landing
with random engine failure and a landing on an asteroid with unknown environmental dynamics. We also
demonstrate the ability of a RL meta-learning optimized policy to implement a guidance law using observations
consisting of only Doppler radar altimeter readings in a Mars landing environment, and LIDAR altimeter
readings in an asteroid landing environment thus integrating guidance and navigation. Keywords: Guidance | Meta learning | Reinforcement learning | Landing guidance |
مقاله انگلیسی |
8 |
A support system for civil aviation navigation equipment security management
یک سیستم پشتیبانی برای مدیریت امنیت تجهیزات ناوبری هواپیمایی کشوری-2020 Civil aviation navigation equipment system has many weaknesses, which easily causes serious problem to air transportation safety. This paper focuses on a support system for civil aviation navigation equipment security management. Firstly, a sustainability assessment platform was constructed to analysis and find out the weak- nesses of equipment network. Next, one network expansion planning platform was built to improve the relia- bility and business continuity of the whole navigation system. Experiments were carried out based on these two platforms. Also, the equipment network of China’s eastern part was expanded based on the business continuity assessment. Results proved that the network business continuity and node efficiencies of new equipment net- work can satisfy the lowest requirement of economic consumption. Finally, the optimal network expansion planning method has been achieved, proving the effectiveness of the civil aviation navigation equipment security management support system. Keywords: Civil aviation safety | Navigation equipment system | Sustainability assessment | Equipment expansion planning |
مقاله انگلیسی |
9 |
Methadone treatment of arrestees: A randomized clinical trial
درمان متادون از دستگیر شدگان: یک کارآزمایی بالینی تصادفی-2020 Background: Opioid use disorder is common among detainees in US jails, yet methadone treatment is rarely
initiated.
Methods: This is a three-group randomized controlled trial in which 225 detainees in Baltimore treated for
opioid withdrawal were assigned to: (1) interim methadone (IM) with patient navigation (IM+PN); (2) IM; or
(3) enhanced treatment-as-usual (ETAU). Participants in both IM groups were able to enter standard methadone
treatment upon release, while ETAU participants received an assessment/referral number. Follow-up assessments
at 1, 3, 6, and 12 months post-release determined treatment enrollment, urine drug testing results, selfreported
days of drug use, criminal activity, and overdose events. Generalized linear mixed modelling examined
two planned contrasts: (1) IM groups combined vs. ETAU; and (2) IM+PN vs. IM.
Results: On an intention-to-treat basis, compared to ETAU, significantly more participants in the combined IM
groups were in treatment 30 days post-release, while the IM+PN vs. IM groups did not significantly differ. By
month 12, there were no significant differences in the estimated marginal means of enrollment in any kind of
drug treatment (0.40 and 0.27 for IM+PN and IM groups, respectively, compared to 0.29 for ETAU). There
were no significant differences for either contrast in opioid-positive tests, although all groups reported a sharp
decrease in heroin use from baseline to follow-up. There were five fatal overdoses, but none occurred during
methadone treatment.
Conclusion: Initiating methadone treatment in jail was effective in promoting entry into community-based drug
abuse treatment but subsequent treatment discontinuation attenuated any potential impact of such treatment. Keywords: Interim methadone treatment | Patient navigation | Criminal justice | Jail | Overdose death | Opioid use disorder |
مقاله انگلیسی |
10 |
Surgical Phase Recognition Method with a Sequential Consistency for CAOS-AI Navigation System
روش تشخیص مرحله جراحی با یک سازگاری متوالی برای سیستم ناوبری CAOS-AI-2020 The procedure of orthopedic surgery is quite
complicated, and many kinds of equipment have been used.
Operating room nurses who deliver surgical instruments to surgeon
are supposed to be forced to incur a heavy burden. There are some
studies to recognize surgical phase with convolutional neural
network (CNN) in minimally invasive laparoscopic surgery only.
Previously, we proposed a computer-aided orthopedic surgery
(CAOS)-AI navigation system based on CNN. However, the work
propose a method to improve accuracy of phase recognition by
considering temporal dependency of orthopedic surgery video
acquired from surgeon-wearable video camera. The method
estimates current surgical phase by combining both temporal
dependency and convolutional-long-short term memory network
(CNN-LSTM). Experimental results shows a phase recognition
accuracy of 59.9% by the proposed method applied in unicomapartmenatal
knee arthroplasty (UKA). Keywords: Deep Learning | Computer-aided Orthopaedic Surgery | Operating Room Nurse | Phase Recognition |
مقاله انگلیسی |