Passive Camera Research Articles

Thermal imaging analysis of ballast fouling: Investigating the effects of parent rock and fouling materials through IRT passive camera

This study explores the use of infrared thermography (IRT) technology for the non-destructive evaluation of ballast fouling in railway tracks, focusing on the influence of parent rock types and fouling materials. Utilizing thermal imaging, the research investigates how variations in ballast conditions affect surface temperature, which serves as an indicator of structural integrity and health. The experimental setup involved ballast samples derived from three different rock types—basalt, limestone, and andesite—fouled with commonly encountered materials like sand and clay at varying percentages. Results demonstrate that fouling level and type significantly influence the thermal signatures captured by IRT passive camera. Notably, ballast derived from darker rocks exhibited higher temperatures, indicating greater emissivity, while fouled ballast showed distinct temperature patterns compared to clean samples, emphasizing the potential of thermal imaging in detecting and quantifying fouling in ballast layers. This research underscores the viability of IRT passive camera in the routine maintenance and monitoring of railway infrastructure, providing a foundation for further development of integrated diagnostic tools for railway management systems.

Optimizing Strawberry Disease and Quality Detection with Vision Transformers and Attention-Based Convolutional Neural Networks.

Machine learning and computer vision have proven to be valuable tools for farmers to streamline their resource utilization to lead to more sustainable and efficient agricultural production. These techniques have been applied to strawberry cultivation in the past with limited success. To build on this past work, in this study, two separate sets of strawberry images, along with their associated diseases, were collected and subjected to resizing and augmentation. Subsequently, a combined dataset consisting of nine classes was utilized to fine-tune three distinct pretrained models: vision transformer (ViT), MobileNetV2, and ResNet18. To address the imbalanced class distribution in the dataset, each class was assigned weights to ensure nearly equal impact during the training process. To enhance the outcomes, new images were generated by removing backgrounds, reducing noise, and flipping them. The performances of ViT, MobileNetV2, and ResNet18 were compared after being selected. Customization specific to the task was applied to all three algorithms, and their performances were assessed. Throughout this experiment, none of the layers were frozen, ensuring all layers remained active during training. Attention heads were incorporated into the first five and last five layers of MobileNetV2 and ResNet18, while the architecture of ViT was modified. The results indicated accuracy factors of 98.4%, 98.1%, and 97.9% for ViT, MobileNetV2, and ResNet18, respectively. Despite the data being imbalanced, the precision, which indicates the proportion of correctly identified positive instances among all predicted positive instances, approached nearly 99% with the ViT. MobileNetV2 and ResNet18 demonstrated similar results. Overall, the analysis revealed that the vision transformer model exhibited superior performance in strawberry ripeness and disease classification. The inclusion of attention heads in the early layers of ResNet18 and MobileNet18, along with the inherent attention mechanism in ViT, improved the accuracy of image identification. These findings offer the potential for farmers to enhance strawberry cultivation through passive camera monitoring alone, promoting the health and well-being of the population.

Living on the edge: nature preserves as an oasis for birds, bats, and other mammals in the urban desert and concrete jungle

Increasing urbanization threatens a variety of vital vertebrate habitats, including those of birds, and both terrestrial and aerial mammals. Nature preserves near urban centers at the rural/urban interface may harbor natural areas which can help to offset loss of habitat as cities expand. Therefore, techniques which allow managers to conduct short term surveys for vertebrates are needed. I conducted non-invasive, passive camera trapping and acoustic surveys in the vicinity of the urban area of Charlotte, North Carolina across 8 sites within Mecklenburg, Cabarrus, and Union counties during summer to fall 2023 to collect data on avian and mammalian communities. Five species of bats were documented, alongside 39 birds, and 11 terrestrial mammals. Bat activity decreased consistently along the sample period whereas terrestrial mammals were consistently sampled during the same time frame, with early summer providing effective data on avian presence. Automated identification software followed by manually vetting for bats and birds was effective in documenting diversity alongside camera trapping. The results presented here provide baseline data for future monitoring to inform urban planning management strategies and future studies on the potential presence of avian and mammalian presence in nature preserves.

Camera-Based Net Avoidance Controls of Underwater Robots.

Fishing nets are dangerous obstacles for an underwater robot whose aim is to reach a goal in unknown underwater environments. This paper proposes how to make the robot reach its goal, while avoiding fishing nets that are detected using the robot's camera sensors. For the detection of underwater nets based on camera measurements of the robot, we can use deep neural networks. Passive camera sensors do not provide the distance information between the robot and a net. Camera sensors only provide the bearing angle of a net, with respect to the robot's camera pose. There may be trailing wires that extend from a net, and the wires can entangle the robot before the robot detects the net. Moreover, light, viewpoint, and sea floor condition can decrease the net detection probability in practice. Therefore, whenever a net is detected by the robot's camera, we make the robot avoid the detected net by moving away from the net abruptly. For moving away from the net, the robot uses the bounding box for the detected net in the camera image. After the robot moves backward for a certain distance, the robot makes a large circular turn to approach the goal, while avoiding the net. A large circular turn is used, since moving close to a net is too dangerous for the robot. As far as we know, our paper is unique in addressing reactive control laws for approaching the goal, while avoiding fishing nets detected using camera sensors. The effectiveness of the proposed net avoidance controls is verified using simulations.

Seeing Photons in Color

Megapixel single-photon avalanche diode (SPAD) arrays have been developed recently, opening up the possibility of deploying SPADs as generalpurpose passive cameras for photography and computer vision. However, most previous work on SPADs has been limited to monochrome imaging. We propose a computational photography technique that reconstructs high-quality color images from mosaicked binary frames captured by a SPAD array, even for high-dyanamic-range (HDR) scenes with complex and rapid motion. Inspired by conventional burst photography approaches, we design algorithms that jointly denoise and demosaick single-photon image sequences. Based on the observation that motion effectively increases the color sample rate, we design a blue-noise pseudorandom RGBW color filter array for SPADs, which is tailored for imaging dark, dynamic scenes. Results on simulated data, as well as real data captured with a fabricated color SPAD hardware prototype shows that the proposed method can reconstruct high-quality images with minimal color artifacts even for challenging low-light, HDR and fast-moving scenes. We hope that this paper, by adding color to computational single-photon imaging, spurs rapid adoption of SPADs for real-world passive imaging applications.

Assessing the implications of sexual segregation when surveying white‐tailed deer Odocoileus virginianus

Baited camera surveys are often used to study white‐tailed deer Odocoileus virginianus populations and inform harvest decisions. Surveys are commonly conducted in late summer or early fall when deer populations are expected to be segregated sexually, whereas hunting seasons typically occur during the breeding season when sexes are likely to be mixed. However, the effects of socio‐sexual shifts in space use on pre‐season camera surveys has not been evaluated. We conducted a baited survey before the hunting season followed by passive camera surveys during the hunting season on three properties in southwestern Georgia, USA. We collected 51 106 images of deer before and during the hunting season from baited and passive cameras. Based on interpolated maps of camera detections, the populations were highly segregated during the September baited surveys. In contrast, subsequent passive camera surveys indicated high overlap of males and females during the breeding months, with males shifting their distribution towards females. Because most management units on private lands are substantially smaller than our camera arrays (typically < 1000 ha), our results suggest that pre‐season surveys may not accurately reflect the population available for harvest during the hunting season. Establishment of cooperative management programs among adjacent landholdings may improve management effectiveness. In addition, managers should anticipate shifts in male distributions during the breeding months and real‐time analytical approaches could be developed with the use of cellular‐based cameras to rapidly alter harvest objectives.

Solo-surgeon pure laparoscopic donor nephrectomy using passive camera holder: IDEAL stage 2a study

BackgroundSolo-surgery can be defined as a practice of a surgeon operating alone using a camera holder, without other surgical members except for a scrub nurse. This study was designed to evaluate the feasibility and safety of solo-surgeon pure laparoscopic donor nephrectomy.MethodsThe study protocol was approved by the Institutional Review Board of Asan Medical Center, Seoul, Korea. The brief study protocol was registered on the Clinical Research Information Service site of the Korea Centers for Disease Control and Prevention. Candidates fulfilling all inclusion and exclusion criteria were enrolled in the clinical trial and underwent solo-surgeon pure laparoscopic donor nephrectomy. The feasibility was assessed by the proportion of subjects who could undergo solo-surgeon pure laparoscopic donor nephrectomy without difficulty. The perioperative complications were identified to assess the safety of solo-surgeon pure laparoscopic donor nephrectomy.ResultsOf the 47 potential candidates from November 2018 to August 2019, 40 were enrolled in the clinical trial and seven excluded due to declining participation. The feasibility of solo-surgeon pure laparoscopic donor nephrectomy was 100%, without an occasion of any difficulty requiring conversion to the human assisted pure laparoscopic donor nephrectomy. Fourteen intraoperative complications occurred in 10 patients. The most common intraoperative complication was spleen injury. Two of three cases classified as the Satava classification grade II were due to the incomplete stapling of endoscopic stapler. Seventy-eight postoperative complications occurred in 34 patients. The most common postoperative complication was nausea/vomiting and followed by aspartate aminotransferase/alanine aminotransferase elevation. Most postoperative complication was independent of the solo-surgery itself.ConclusionsSolo-surgeon pure laparoscopic donor nephrectomy using passive camera holder is technically feasible. In terms of safety, it is necessary to adjust the scope of surgery performed alone.Trial Registration CRIS, KCT0003458. Registered 30/01/2019, Retrospectively registered, https://cris.nih.go.kr/cris/search/detailSearch.do/15868.

Enhancing the accuracy of forging measurement using silhouettes in images

In this study, a new passive camera system for heavy cylindrical forging measurement, based on silhouettes in images, is developed. New methods for making such a system more resistant to the negative effects of the industrial environment have been proposed. This includes weighted edge filtering based on complementary information about the edge quality in an image. The recorded measurement median errors were ±0.12 mm and ±0.14 mm. Moreover, the 95% confidence intervals were ±0.5 mm and ±1 mm for the forging axis and diameter measurements, respectively. Both results were achieved in a measurement volume of 6 × 6 × 2 m during the measurement of glowing hot forgings in industrial conditions. The results surpass those of the state-of-the-art method, mainly in the case of axis straightness measurement, by approximately 50%. The measurement is fast, and it provides feedback about the axis straightness for its subsequent correction.

Detection of Physical Strain and Fatigue in Industrial Environments Using Visual and Non-Visual Low-Cost Sensors

The detection and prevention of workers’ body straining postures and other stressing conditions within the work environment, supports establishing occupational safety and promoting well being and sustainability at work. Developed methods towards this aim typically rely on combining highly ergonomic workplaces and expensive monitoring mechanisms including wearable devices. In this work, we demonstrate how the input from low-cost sensors, specifically, passive camera sensors installed in a real manufacturing workplace, and smartwatches used by the workers can provide useful feedback on the workers’ conditions and can yield key indicators for the prevention of work-related musculo-skeletal disorders (WMSD) and physical fatigue. To this end, we study the ability to assess the risk for physical strain of workers online during work activities based on the classification of ergonomically sub-optimal working postures using visual information, the correlation and fusion of these estimations with synchronous worker heart rate data, as well as the prediction of near-future heart rate using deep learning-based techniques. Moreover, a new multi-modal dataset of video and heart rate data captured in a real manufacturing workplace during car door assembly activities is introduced. The experimental results show the efficiency of the proposed approach that exceeds 70% of classification rate based on the F1 score measure using a set of over 300 annotated video clips of real line workers during work activities. In addition a time lagging correlation between the estimated ergonomic risks for physical strain and high heart rate was assessed using a larger dataset of synchronous visual and heart rate data sequences. The statistical analysis revealed that imposing increased strain to body parts will results in an increase to the heart rate after 100–120 s. This finding is used to improve the short term forecasting of worker’s cardiovascular activity for the next 10 to 30 s by fusing the heart rate data with the estimated ergonomic risks for physical strain and ultimately to train better predictive models for worker fatigue.

Early experience of solo surgeon laparoscopic PPPD with articulated scope holding arm system: The feasibility and safety of short term surgical outcomes

Surgeons performing laparoscopic PPPD usually requires two or three surgical assistants. However, those who perform the solo surgeon laparoscopic PPPD (SSLPD) simply need a scrub nurse because a passive camera holder can hold camera stably instead of surgical assistants. In this study, we investigate the feasibility and safety of the SSLPD with articulated scope holding arm system. From April 2017 to July 2019, 11 patients underwent minimal invasive PPPD in our hospital. Among them, 9 patients underwent SSLPD and 1 patient underwent robotic single port plus 2 ports hybrid PPPD and 1 robotic single port plus 2 ports PPPD. The above 9 patients underwent SSLPD using passive camera holder (UNITRAC, Carl-Braun-Straße 1, 34212 Melsungen, Hessen, Germany) which facilitate single-handed repositioning. And 1 patient underwent SSLPD using robotic single site surgical system (the da Vinci Xi Surgical System; Intuitive Surgical, Sunnyvale, CA, USA). Viewing by using a device such as Grasper was achieved by pulling and fixing Grasper using a towel click. Five patients were female and the rest were male. Five patients were diagnosed ampulla of vater caner, two were pancreatic cancer, one was common bile duct cancer, one was duodenal cancer and one had mucinous non-neoplastic cyst. And the mean operation time was 644 minutes and the mean estimated blood loss was 863 mL and mean length of hospital stay was 13.2 days. There was no major complication except one patient developed postoperative bleeding but recovered after conservative treatment. The SSLPD procedure using passive camera holder is feasible and safety.

Temporal interactions and moon illumination effect on mammals in a tropical semievergreen forest of Manas National Park, Assam, India

AbstractSpecies interactions play a vital role in structuring mammalian communities by stimulating behavioral responses in varied niche dimensions that affect sympatric associations and predator–prey relationships. We determined temporal overlap and effects of the moon cycle on dominant and sub‐dominant mammalian assemblages in Manas National Park, India. A total of 36 species were captured, with 24,865 independent records over 11,294 trap nights. We collected 1,130 photographs of five large‐ and medium‐sized carnivores and 1,541 photographs of 12 small carnivores. Fifty‐one percent of records were detected during diurnal period, followed by 38% in nocturnal phase, and 11% during twilight. Small carnivores such as Prionailurus bengalensis and Viverridae spp. were strictly nocturnal, whereas Martes flavigula and Herpestidae spp. were diurnal. Medium‐sized carnivores were either nocturnal (Neofelis nebulosa) or diurnal (Cuon alpinus), whereas large‐sized carnivores (Panthera tigris, Panthera pardus, and Ursus thibetanus) were cathemeral. A high degree of temporal overlap (>0.75) was found between most sympatric carnivores with distinct activity peaks, while a low overlap (<0.50) was observed between different body‐sized carnivores. Viverrids’ activity was negatively correlated (r = −0.44, p < 0.01) with lunar cycles, perhaps to increase foraging efficiency or as an anti‐predator strategy. Large prey (μ = 133.23°) and small prey (μ = 131.35°) activity were high during brighter nights due to better visual detection in detecting or avoiding predators. Dominant species activity was least affected by the lunar cycle among forest‐dependent mammals, whereas subdominant species activity was either lunarphobic or lunarphilic. The study demonstrates the use of passive camera traps in understanding the behavioral rhythms of tropical mammals.

Radiometry and Photometry for Autonomous Vehicles and Machines - Fundamental Performance Limits

As autonomous vehicles and machines, such as self-driving cars, agricultural drones and industrial robots, become ubiquitous, there is an increasing need to understand the objective performance of cameras to support these functions. Images go beyond aesthetic and subjective roles as they assume increasing aspects of control, safety, and diagnostic capabilities. Radiometry and photometry are fundamental to describing the behavior of light and modeling the signal chain for imaging systems, and as such, are crucial for establishing objective behavior. As an engineer or scientist, having an intuitive feel for the magnitude of units and the physical behavior of components or systems in any field improves development capabilities and guards against rudimentary errors. Back-of-the-envelope estimations provide comparisons against which detailed calculations may be tested and will urge a developer to “try again” if the order of magnitude is off for example. They also provide a quick check for the feasibility of ideas, a “giggle” or “straight-face” test as it is sometimes known. This paper is a response to the observation of the authors that, amongst participants that are newly relying on the imaging field and existing image scientists alike, there is a general deficit of intuition around the units and order of magnitude of signals in typical cameras for autonomous vehicles and the conditions within which they operate. Further, there persists a number of misconceptions regarding general radiometric and photometric behavior. Confusion between the inverse square law as applied to illumination and consistency of image luminance versus distance is a common example. The authors detail radiometric and photometric model for an imaging system, using it to clarify vocabulary, units and behaviors. The model is then used to estimate the number of quanta expected in pixels for typical imaging systems for each of the patches of a MacBeth color checker under a wide variety of illumination conditions. These results form the basis to establish the fundamental limits of performance for passive camera systems based both solely on camera geometry and additionally considering typical quantum efficiencies available presently. Further a mental model is given which will quickly allow user to estimate numbers of photoelectrons in pixel.

Installing chainsaw‐carved hollows in medium‐sized live trees increases rates of visitation by hollow‐dependent fauna

Anthropogenic disturbance has resulted in a global reduction in the abundance of mature, hollow‐bearing trees. Nest boxes have long been used to provide supplementary shelter sites in revegetated and regenerating landscapes, but limitations in their effectiveness when offsetting the loss of mature trees has led to increased interest in novel designs of artificial hollows. For example, mechanically excavating cavities into the trunk or branches of trees. However, the effectiveness of artificial hollows in attracting wildlife to visit small‐ or medium‐sized, growing trees in human‐disturbed landscapes has received little attention. In this study, we installed chainsaw hollows that were designed for small, hollow‐dependent mammals and birds into the trunks of live medium‐sized trees. We conducted a before‐after control‐impact experiment using passive camera traps to monitor changes in visitations by wildlife to (1) mature hollow‐bearing trees, (2) developing trees without hollows (i.e. control trees), and (3) developing trees with newly installed chainsaw hollows. We found that, compared to large hollow‐bearing trees and control trees, the developing trees that were selected for chainsaw hollow construction showed the greatest visitation rates by hollow‐dependent wildlife (i.e. number of visits) during the “post‐impact” surveys. Our results suggest that chainsaw hollows designed to replicate the external physical characteristics of natural tree hollows could be effective in attracting target hollow‐dependent fauna to developing trees in regenerating and revegetated landscapes. Further studies are required to compare the effectiveness of natural hollows, chainsaw hollows, and nest boxes when deployed in a range of human‐disturbed landscapes.

Centralized visual based navigation and control of a swarm of satellites for on-orbit servicing

In the framework of on-orbit proximity operations, small satellites represent an appealing solution in terms of costs, effectiveness and realization, but show intrinsic power, mass and computation limitations that could be overcome if cooperation among many spacecraft is considered. In this research, a swarm of small satellites (called “Children S/C″), deployed from a larger platform (called “Mother S/C″), is employed in the inspection of a damaged spacecraft, which cannot be directly approached by the Mother S/C for safety reasons. The navigation process is delegated to the Mother S/C, that is equipped with a passive camera. A navigation algorithm runs on the Mother S/C, which identifies and tracks the Children S/C framed in the scene, even though false matches (i.e., incorrect tracking of a given child) could happen. The navigation algorithm is made robust through the generation at each time step of a propagated virtual image (based on the previous estimate of the swarm state) which is compared to the acquired image for the correct identification of each child. When the relative position estimates reach a satisfactory accuracy, the Mother S/C communicates to the Children S/C their current state and an optimal impulsive control strategy can be implemented to make the swarm fulfill the required inspection task. Simulations are carried out in a purposely developed software environment, in which images of rendered CAD models are acquired and processed to have a realistic validation of the estimation algorithm, showing satisfactory performance and robustness for the overall mission accomplishment.

CHANGES IN OPEN FIELD BEHAVIOR AND DECLARATIVE MEMORY IN “DEPRESSIVE” RATS WITH HIGH IMMOBILITY AND DECREASED LEVEL OF BRAIN MONOAMINES

INTRODUCTION Changes in some forms of motivational-emotional behavior, learning and memory are thought to be characteristic for major depressive disease. However, results existing until today about the character of changes in motivational-emotional and exploratory behavior as well as character of disorders in declarative memory, accompanying major depressive disease, are not unambiguous. Therefore, studying them in animal models of depression is very topical and important. METHODS Experiments were conducted on adult white wild rats (with 250-300 g weight). “Depressive” and “non- depressive” rats were selected according to the level of immobility in forced swim test. Rats with low level of immobility, “non-depressive” rats, constituted control group and rats with high level of immobility, “depressive” rats, constituted the experimental group (10 rats in each). Changes of motivational-emotional and exploratory behavior were studied in open field test. The changes of learning and memory were studied in the fear motivated one trial passive avoidance test considered as the declarative memory test. Experiments were carried out on “non-depressive”, control and “depressive”, experimental groups (10 rats in each). Obtained results were processed statistically by Student’s t-test. RESULTS Sharp decrease in locomotion was found in rats with high level of immobility. It was manifested in a significant decrease of the number of crossed squares. The quantitative indices of vertical activity, vertical standings, head risings, were also sharply decreased. Fear reaction was considerably increased in “depressive” rats, manifested in the significant decrease of the number of entering in the center of open field and grooming and sharp increase in defecation rate. Investigation of the changes of learning and memory in the passive avoidance test has shown that the latency of entering from the light into dark section of passive avoidance camera, in the learning session, was sharply increased in “depressive” rats. They revealed an impaired ability to evaluate the level of danger coming from the brightly illuminated open area and therefore they do not hurry to escape from the dangerous section. The difference between “depressive” and “non-depressive” rats was maintained even after 24 hours from receiving a painful stimulation. In particular, the animals of control group remember that they have received a painful stimulation in dark section during learning session and do not enter there during testing session, whereas the experimental animals with considerable delay but still enter in the dark section during testing session, therefore, they show significant impairment of declarative memory in passive avoidance task. CONCLUSIONS Locomotor and exploratory behavior are impaired and fear motivation is increased in the open field in “depressive” rats with high immobility and low level of monoamines content in the brain. Learning and memory in one of the tests of declarative memory, so called passive avoidance task, is disturbed.

Inexpensive, Underwater Filming of Rare Fishes in High Definition

Generating public interest in fish and their biology is often challenging. Many aquatic species are cryptic and largely invisible to the public. Therefore, increasing public awareness of cryptic fishes and elevating their visibility to broad audiences requires innovation. Inexpensive technological advancements now provide fisheries biologists, managers, and researchers with means never before possible for documenting fish in their natural habitat via underwater videography. We investigated cost efficient and simple methods for capturing and creating high quality, high definition, and informative underwater videos that could be used by people with little or no previous experience in videography. We tested 1) a variety of filming equipment including cameras and camera recording settings, lenses, batteries, and memory cards; 2) active and passive camera deployment techniques; and 3) a variety of free and paid postproduction software and compared them for ease of use, expense, and quality of output. Highest quality footage, i.e., highest resolution, clearest, and most stable, was obtained using a GoPro action camera deployed underwater in a stationary position mounted to a metal base plate using a combination of stock and macro lenses, and filming in 4K resolution at 30 frames per second. Final production videos were created using Adobe Premiere Pro.

Autonomous relative navigation around uncooperative spacecraft based on a single camera

The interest of the space community toward missions like On-Orbit Servicing of functional satellite to extend their operative life, or Active Debris Removal to reduce the risk of collision among artificial objects in the most crowded orbital belts, is significantly increasing for both economical and safety aspects. These activities present significant technical challenges and, thus, can be enabled only by increasing the level of autonomy and robustness of space systems in terms of guidance, navigation and control functionalities. Clearly this goal requires the design and development of ad-hoc technologies and algorithms. In this framework, this paper presents an original architecture for relative navigation based on a single passive camera able to fully reconstruct the relative state between a chaser spacecraft and a non-cooperative, known target. The proposed architecture is loosely coupled, meaning that pose determination and full relative state estimation are entrusted to separate, but rigidly interconnected processing blocks. Innovative aspects are relevant to both the pose determination algorithms and the filtering scheme. Preliminary performance assessment is carried out by means of numerical simulations considering multiple realistic target/chaser relative dynamics and target geometries. Results allow demonstrating robustness against measurement error sources caused possibly by image processing as well as fast rotational dynamics.

Photon-counting panoramic three-dimensional imaging using a Geiger-mode avalanche photodiode array

A lidar system based on a photon-counting Geiger-mode avalanche photodiode (GmAPD) array can provide high range resolution three-dimensional imaging. The small number of pixels in the GmAPD array limits the size of measured scenes compared to passive cameras. Here, the performance of rapid panoramic imaging of larger scenes is investigated. Controlled environment indoor measurement at up to 24 m range is used to validate the principle. Outdoor daylight measurements of natural targets at 230 to 340 m range are performed to test the capability of the measurement system. A 20 deg by 1.8 deg scene is imaged with 0.25-mrad lateral resolution in 4 s. The standard deviation of point to plane distances for a flat wall in the outdoor measurement is 10.6 mm, giving an estimate of the achievable relative range accuracy, even if this will depend on the signal-to-noise ratio. A radiometric model is used to estimate the performance of an upgraded optimized system and the necessary laser power for imaging at longer ranges in both day and night conditions.

A passive camera based determination of a non-cooperative and unknown satellite's pose and shape

The relevance of autonomy in space systems during rendezvous and docking operations has been lately increasing. At the scope, a robust GNC architecture is required, which strictly relies on the navigation system's performance and must assure both high efficiency and safety, i.e. low errors and no collisions with the target satellite. One of the most explored fields is the optical navigation one. Using passive optical sensors such as cameras can give high benefit in terms of characterization of the observed scene, thus enlarging the consciousness of what is going on in the mission scenario. The present research investigates the development of a filter which can estimate the shape and relative attitude, position and velocity of a non-cooperative, possibly unknown satellite orbiting around Earth, observed by a camera and a distance sensor mounted on a chaser satellite, whose objective is to successfully complete a docking maneuver. The image taken at a certain time is processed, features are extracted from it and matched with the ones extracted from the image at the previous time step. The matched features along with the relative distance measured by the distance sensor are merged inside an unscented Kalman filter, which predicts, updates and improves the state's estimate throughout the iterations. The expedient used in the filter is to give a 3D characterization to the 2D features used as measurements. The filter estimates the 3D coordinates of these points, i.e. the target's shape, in the camera reference frame, which depend on the target's attitude dynamics and the chaser's relative orbital dynamics. Thus, the target's attitude parameters, i.e. the quaternions, and angular velocity vector, the relative position and velocity vectors and the tracked 3D points are all included in the state vector and estimated by the filter. Subsequently, the 3D point coordinates are determined in the body reference frame. By doing this for all the tracked points, a 3D map of the target can be built.

EXPERIENCES WITH ACQUIRING HIGHLY REDUNDANT SPATIAL DATA TO SUPPORT DRIVERLESS VEHICLE TECHNOLOGIES

Abstract. As vehicle technology is moving towards higher autonomy, the demand for highly accurate geospatial data is rapidly increasing, as accurate maps have a huge potential of increasing safety. In particular, high definition 3D maps, including road topography and infrastructure, as well as city models along the transportation corridors represent the necessary support for driverless vehicles. In this effort, a vehicle equipped with high-, medium- and low-resolution active and passive cameras acquired data in a typical traffic environment, represented here by the OSU campus, where GPS/GNSS data are available along with other navigation sensor data streams. The data streams can be used for two purposes. First, high-definition 3D maps can be created by integrating all the sensory data, and Data Analytics/Big Data methods can be tested for automatic object space reconstruction. Second, the data streams can support algorithmic research for driverless vehicle technologies, including object avoidance, navigation/positioning, detecting pedestrians and bicyclists, etc. Crucial cross-performance analyses on map database resolution and accuracy with respect to sensor performance metrics to achieve economic solution for accurate driverless vehicle positioning can be derived. These, in turn, could provide essential information on optimizing the choice of geospatial map databases and sensors’ quality to support driverless vehicle technologies. The paper reviews the data acquisition and primary data processing challenges and performance results.