scholarly journals Computationally Efficient Iterative Pose Estimation for Space Robot Based on Vision

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Xiang Wu ◽  
Ning Wu
Keyword(s):  
Pose Estimation ◽  
Error Function ◽  
Outer Space ◽  
Space Robot ◽  
Space Environment ◽  
Experimental Result ◽  
Computational Time ◽  
Computationally Efficient ◽  
Absolute Orientation ◽  
The Absolute

In postestimation problem for space robot, photogrammetry has been used to determine the relative pose between an object and a camera. The calculation of the projection from two-dimensional measured data to three-dimensional models is of utmost importance in this vision-based estimation however, this process is usually time consuming, especially in the outer space environment with limited performance of hardware. This paper proposes a computationally efficient iterative algorithm for pose estimation based on vision technology. In this method, an error function is designed to estimate the object-space collinearity error, and the error is minimized iteratively for rotation matrix based on the absolute orientation information. Experimental result shows that this approach achieves comparable accuracy with the SVD-based methods; however, the computational time has been greatly reduced due to the use of the absolute orientation method.

scholarly journals A computationally efficient hybrid 2D–3D subwoofer model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ahmad H. Bokhari ◽  
Martin Berggren ◽  
Daniel Noreland ◽  
Eddie Wadbro
Keyword(s):  
Hybrid Model ◽  
3D Model ◽  
Element Model ◽  
Acoustic Properties ◽  
Computational Time ◽  
Average Response ◽  
Frequency Range ◽  
Computationally Efficient ◽  
Lumped Element ◽  
Lumped Element Model

AbstractA subwoofer generates the lowest frequency range in loudspeaker systems. Subwoofers are used in audio systems for live concerts, movie theatres, home theatres, gaming consoles, cars, etc. During the last decades, numerical simulations have emerged as a cost- and time-efficient complement to traditional experiments in the design process of different products. The aim of this study is to reduce the computational time of simulating the average response for a given subwoofer design. To this end, we propose a hybrid 2D–3D model that reduces the computational time significantly compared to a full 3D model. The hybrid model describes the interaction between different subwoofer components as interacting modules whose acoustic properties can partly be pre-computed. This allows us to efficiently compute the performance of different subwoofer design layouts. The results of the hybrid model are validated against both a lumped element model and a full 3D model over a frequency band of interest. The hybrid model is found to be both accurate and computationally efficient.

The parameter identification model considering both geometric parameters and joint stiffness

2019 ◽  
Vol 47 (1) ◽  
pp. 76-81
Author(s):  
Jing Bai ◽  
Le Fan ◽  
Shuyang Zhang ◽  
Zengcui Wang ◽  
Xiansheng Qin
Keyword(s):  
Parameter Identification ◽  
Industrial Robot ◽  
Joint Stiffness ◽  
Geometric Parameters ◽  
Least Square ◽  
Experimental Result ◽  
Positional Accuracy ◽  
Content Type ◽  
The Absolute ◽  
Identification Model

Purpose Both geometric and non-geometric parameters have noticeable influence on the absolute positional accuracy of 6-dof articulated industrial robot. This paper aims to enhance it and improve the applicability in the field of flexible assembling processing and parts fabrication by developing a more practical parameter identification model. Design/methodology/approach The model is developed by considering both geometric parameters and joint stiffness; geometric parameters contain 27 parameters and the parallelism problem between axes 2 and 3 is involved by introducing a new parameter. The joint stiffness, as the non-geometric parameter considered in this paper, is considered by regarding the industrial robot as a rigid linkage and flexible joint model and adds six parameters. The model is formulated as the form of error via linearization. Findings The performance of the proposed model is validated by an experiment which is developed on KUKA KR500-3 robot. An experiment is implemented by measuring 20 positions in the work space of this robot, obtaining least-square solution of measured positions by the software MATLAB and comparing the result with the solution without considering joint stiffness. It illustrates that the identification model considering both joint stiffness and geometric parameters can modify the theoretical position of robots more accurately, where the error is within 0.5 mm in this case, and the volatility is also reduced. Originality/value A new parameter identification model is proposed and verified. According to the experimental result, the absolute positional accuracy can be remarkably enhanced and the stability of the results can be improved, which provide more accurate parameter identification for calibration and further application.

scholarly journals A Multidimensional and Multiscale Model for Pressure Analysis in a Reservoir-Pipe-Valve System

2018 ◽  
Author(s):  
Feng Jie Zheng ◽  
Fu Zheng Qu ◽  
Xue Guan Song
Keyword(s):  
Pressure Fluctuation ◽  
Large Scale ◽  
Three Dimensional ◽  
Industrial Process ◽  
Multiscale Model ◽  
Computational Time ◽  
Small Scale ◽  
Cfd Model ◽  
Computationally Efficient ◽  
Proposed Model

Reservoir-pipe-valve (RPV) systems are widely used in many industrial process. The pressure in an RPV system plays an important role in the safe operation of the system, especially during the sudden operation such as rapid valve opening/closing. To investigate the pressure especially the pressure fluctuation in an RPV system, a multidimensional and multiscale model combining the method of characteristics (MOC) and computational fluid dynamics (CFD) method is proposed. In the model, the reservoir is modeled by a zero-dimensional virtual point, the pipe is modeled by a one-dimensional MOC, and the valve is modeled by a three-dimensional CFD model. An interface model is used to connect the multidimensional and multiscale model. Based on the model, a transient simulation of the turbulent flow in an RPV system is conducted, in which not only the pressure fluctuation in the pipe but also the detailed pressure distribution in the valve are obtained. The results show that the proposed model is in good agreement with the full CFD model in both large-scale and small-scale spaces. Moreover, the proposed model is more computationally efficient than the CFD model, which provides a feasibility in the analysis of complex RPV system within an affordable computational time.

scholarly journals IMAGE-BASED ORIENTATION DETERMINATION OF MOBILE SENSOR PLATFORMS

2021 ◽  
Vol XLIII-B1-2021 ◽  
pp. 215-220
Author(s):  
O. Hasler ◽  
S. Nebiker
Keyword(s):  
Sensor Fusion ◽  
Pose Estimation ◽  
Reference System ◽  
Laser Scanner ◽  
Relative Orientation ◽  
Robotic Platform ◽  
Sensor Platforms ◽  
Local Reference ◽  
The Absolute ◽  
Additional Approach

Abstract. Estimating the pose of a mobile robotic platform is a challenging task, especially when the pose needs to be estimated in a global or local reference frame and when the estimation has to be performed while the platform is moving. While the position of a platform can be measured directly via modern tachymetry or with the help of a global positioning service GNSS, the absolute platform orientation is harder to derive. Most often, only the relative orientation is estimated with the help of a sensor mounted on the robotic platform such as an IMU, with one or multiple cameras, with a laser scanner or with a combination of any of those. Then, a sensor fusion of the relative orientation and the absolute position is performed. In this work, an additional approach is presented: first, an image-based relative pose estimation with frames from a panoramic camera using a state-of-the-art visual odometry implementation is performed. Secondly, the position of the platform in a reference system is estimated using motorized tachymetry. Lastly, the absolute orientation is calculated using a visual marker, which is placed in the space, where the robotic platform is moving. The marker can be detected in the camera frame and since the position of this marker is known in the reference system, the absolute pose can be estimated. To improve the absolute pose estimation, a sensor fusion is conducted. Results with a Lego model train as a mobile platform show, that the trajectory of the absolute pose calculated independently with four different markers have a deviation < 0.66 degrees 50% of the time and that the average difference is < 1.17 degrees. The implementation is based on the popular Robotic Operating System ROS.

scholarly journals Protection of Space Environment in the Light of Perspective Challenges of “Space Wars”

2018 ◽  
Vol 5 (2) ◽  
pp. 107-114
Author(s):  
Anna Hurova
Keyword(s):  
Outer Space ◽  
Legal Regulation ◽  
Armed Conflicts ◽  
Space Environment ◽  
International Conflicts ◽  
International Court Of Justice ◽  
Human Environment ◽  
International Court ◽  
Space Objects ◽  
Principle Of Proportionality

In article it is analyzed action in the space of the principle of prohibition of the use of force and threats (jus contra bellum). Also it is researched application of Geneva Law to space conflicts (jus in bello) and it correlations with another hard and soft norms of international law in the light of protection of space environment such as Convention on the Prohibition of Military or Any Other Hostile Use of Environmental Modification Techniques, Declaration of the United Nations Conference on the Human Environment 1972, Rio Declaration on Environment and Development 1992 etc. Beside this it is used practice of International Court of Justice for argumentation of positions and conclusions. Since space objects management is done remotely with help of software, author draw parallels between legal regulation of international conflicts in outer space and cyber space. Furthermore, it is researched specific features of application the principle of proportionality in international space armed conflicts with the aim of protection environment of space and Earth.

scholarly journals A Multidimensional and Multiscale Model for Pressure Analysis in a Reservoir-Pipe-Valve System

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Feng Jie Zheng ◽  
Chao Yong Zong ◽  
William Dempster ◽  
Fu Zheng Qu ◽  
Xue Guan Song
Keyword(s):  
Large Scale ◽  
Pressure Fluctuations ◽  
Three Dimensional ◽  
Multiscale Model ◽  
Computational Time ◽  
Small Scale ◽  
Dimensional System ◽  
Cfd Model ◽  
Computationally Efficient ◽  
Proposed Model

Reservoir-pipe-valve (RPV) systems are widely used in many industrial processes. The pressure in an RPV system plays an important role in the safe operation of the system, especially during the sudden operations such as rapid valve opening or closing. To investigate the pressure response, with particular interest in the pressure fluctuations in an RPV system, a multidimensional and multiscale model combining the method of characteristics (MOC) and computational fluid dynamics (CFD) method is proposed. In the model, the reservoir is modeled as a zero-dimensional virtual point, the pipe is modeled as a one-dimensional system using the MOC, and the valve is modeled using a three-dimensional CFD model. An interface model is used to connect the multidimensional and multiscale model. Based on the model, a transient simulation of the turbulent flow in an RPV system is conducted in which not only the pressure fluctuation in the pipe but also the detailed pressure distribution in the valve is obtained. The results show that the proposed model is in good agreement when compared with a high fidelity CFD model used to represent both large-scale and small-scale spaces. As expected, the proposed model is significantly more computationally efficient than the CFD model. This demonstrates the feasibility of analyzing complex RPV systems within an affordable computational time.

scholarly journals Space resources activities from the perspective of sustainability: legal aspects

2020 ◽  
Vol 3 ◽  
Author(s):  
Mahulena Hofmann ◽  
Federico Bergamasco
Keyword(s):  
Present Article ◽  
Negative Impact ◽  
Outer Space ◽  
Mining Area ◽  
Legal Aspects ◽  
Space Environment ◽  
Environmental Concerns ◽  
Legal Perspective

Non-technical abstract The new forms of the use of outer space, such as space resources activities, not only will provide a vital contribution to research and industry, but could also entail a negative impact to the space environment. The present article aims at discussing from a legal perspective crucial problems such as how we shall ensure that the entities active in the area of space resources take environmental concerns into account, how we shall ensure that they utilize the best possible and least invasive technology and whether they should restore the ‘mining’ area when finishing their tasks.

Efficient Robust Design Optimization of a Stacker–Reclaimer Structure Under Uncertainty

2019 ◽  
Vol 26 (02) ◽  
pp. 1950009
Author(s):  
Soumya Bhattacharjya ◽  
Mithun Sarkar ◽  
Gaurav Datta ◽  
Saibal Kumar Ghosh
Keyword(s):  
Design Optimization ◽  
Robust Design ◽  
Least Squares Method ◽  
Bulk Material ◽  
Robust Design Optimization ◽  
Computational Time ◽  
Computationally Efficient ◽  
Massive Structure ◽  
Accurate Design ◽  
Design Solutions

A stacker–reclaimer structure (SRS) is a massive structure used for bulk material exploration. Performance of SRS is sensitive to the effect of uncertainty which may lead to catastrophic failure consequences. Thus, in this paper a comparatively new robust design optimization (RDO) approach for design of SRS is explored. The involved parameter of SRS e.g., material loading, incrustation, normal digging, etc., may not have well-defined probability density functions and can be expressed as uncertain but bounded (UBB) type parameters. Hence, RDO is explored for probabilistic as well as UBB cases. Solution of such RDO problem in full simulation approach would require extensive computational time. Hence, response surface method (RSM) based metamodeling approach has been adopted here to alleviate computational burden. Also, as conventional least squares method (LSM) based RSM may be a source of error, this study adopts a comparatively new moving LSM (MLSM) based adaptive RSM in RDO. The RDO results depict that UBB type uncertainty is more critical than the probabilistic case. The proposed MLSM based RDO approach yields reasonably accurate design solutions in a computationally efficient way. The proposed MLSM based RDO approach yields design solutions which ensures safe performance of SRS even in the presence of uncertainty.

Parallel Deep Learning Ensembles for Human Pose Estimation

2018 ◽  
Author(s):  
Hailin Ren ◽  
Anil Kumar ◽  
Xinran Wang ◽  
Pinhas Ben-Tzvi
Keyword(s):  
Pose Estimation ◽  
Parallel Architecture ◽  
Body Parts ◽  
Post Processing ◽  
Computationally Efficient ◽  
Human Pose ◽  
Learning Ensembles ◽  
The Individual ◽  
Computational Resources ◽  
Mutually Independent

This paper presents an efficient method to detect human pose with monocular color imagery using a parallel architecture based on deep neural network. The network presented in this approach consists of two sequentially connected stages of 13 parallel CNN ensembles, where each ensemble is trained to detect one specific kind of linkage of the human skeleton structure. After detecting all skeleton linkages, a voting score-based post-processing algorithm assembles the individual linkages to form a complete human structure. This algorithm exploits human structural heuristics while assembling skeleton links and searches only for adjacent link pairs around the expected common joint area. The use of structural heuristics in the presented approach heavily simplifies the post-processing computations. Furthermore, the parallel architecture of the presented network enables mutually independent computing nodes to be efficiently deployed on parallel computing devices such as GPUs for computationally efficient training. The proposed network has been trained and tested on the COCO 2017 person-keypoints dataset and delivers pose estimation performance matching state-of-art networks. The parallel ensembles architecture improves its adaptability in applications aimed at identifying only specific body parts while saving computational resources.

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