Using a robot to learn geometric information from permutations of landmarks

2007 ◽  
pp. 33-45 ◽  
Author(s):  
Benjamín Tovar ◽  
Luigi Freda ◽  
Steven M. LaValle
Keyword(s):  
Geometric Information

On the Shape of Field-Ion Emitters

1976 ◽  
Vol 34 ◽  
pp. 520-521
Author(s):  
H.C. Eaton ◽  
B.N. Ranganathan ◽  
T.W. Burwinkle ◽  
R. J. Bayuzick ◽  
J.J. Hren
Keyword(s):  
Grain Boundary ◽  
Spherical Shape ◽  
Theoretical Strength ◽  
Evaporation Process ◽  
Field Evaporation ◽  
Geometric Information ◽  
Field Ion Microscopy ◽  
Considerable Error ◽  
True Shape ◽  
Ion Microscopy

The shape of the emitter is of cardinal importance to field-ion microscopy. First, the field evaporation process itself is closely related to the initial tip shape. Secondly, the imaging stress, which is near the theoretical strength of the material and intrinsic to the imaging process, cannot be characterized without knowledge of the emitter shape. Finally, the problem of obtaining quantitative geometric information from the micrograph cannot be solved without knowing the shape. Previously published grain-boundary topographies were obtained employing an assumption of a spherical shape (1). The present investigation shows that the true shape deviates as much as 100 Å from sphericity and boundary reconstructions contain considerable error as a result.Our present procedures for obtaining tip shape may be summarized as follows. An empirical projection, D=f(θ), is obtained by digitizing the positions of poles on a field-ion micrograph.

scholarly journals Innovative techniques for the improvement of industrial noise sources identification by beamforming

Noise Mapping ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 129-137
Author(s):  
Giorgio Baldinelli ◽  
Francesco Bianchi ◽  
Danilo Costarelli ◽  
Francesco D’Alessandro ◽  
Flavio Scrucca ◽  
...  
Keyword(s):  
Image Processing ◽  
Noise Source ◽  
Focal Length ◽  
Noise Sources ◽  
Geometric Information ◽  
Industrial Noise ◽  
Sources Identification ◽  
Innovative Technique ◽  
Innovative Techniques

Abstract An innovative technique based on beamforming is implemented, at the aim of detecting the distances from the observer and the relative positions among the noise sources themselves in multisource noise scenarios. By means of preliminary activities to assess the optical camera focal length and stereoscopic measurements followed by image processing, the geometric information in the source-microphone direction is retrieved, a parameter generally missed in classic beamforming applications. A corollary of the method consists of the possibility of obtaining also the distance among different noise sources which could be present in a multisource environment. A loss of precision is found when the effect of the high acoustic reflectivity ground interferes with the noise source.

scholarly journals Orientation-Constrained System for Lamp Detection in Buildings Based on Computer Vision

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1516 ◽  
Author(s):  
Francisco Troncoso-Pastoriza ◽  
Pablo Eguía-Oller ◽  
Rebeca Díaz-Redondo ◽  
Enrique Granada-Álvarez ◽  
Aitor Erkoreka
Keyword(s):  
Computer Vision ◽  
Optimization Methods ◽  
Geometric Information ◽  
Constrained System ◽  
Building Information Modelling ◽  
Correct Model ◽  
Reprojection Error ◽  
Localization Errors ◽  
Building Information ◽  
Error Filtering

Computer vision is used in this work to detect lighting elements in buildings with the goal of improving the accuracy of previous methods to provide a precise inventory of the location and state of lamps. Using the framework developed in our previous works, we introduce two new modifications to enhance the system: first, a constraint on the orientation of the detected poses in the optimization methods for both the initial and the refined estimates based on the geometric information of the building information modelling (BIM) model; second, an additional reprojection error filtering step to discard the erroneous poses introduced with the orientation restrictions, keeping the identification and localization errors low while greatly increasing the number of detections. These enhancements are tested in five different case studies with more than 30,000 images, with results showing improvements in the number of detections, the percentage of correct model and state identifications, and the distance between detections and reference positions.

Collision-Free Tool Path Generation for Five-Axis High Speed Machining

2011 ◽  
Vol 474-476 ◽  
pp. 961-966 ◽  
Author(s):  
Li Qiang Zhang ◽  
Min Yue
Keyword(s):  
Image Analysis ◽  
Collision Detection ◽  
High Speed ◽  
Tool Path ◽  
Geometric Model ◽  
High Speed Machining ◽  
Analysis Method ◽  
Geometric Information ◽  
Detection Approach ◽  
Five Axis

Collision detection is a critical problem in five-axis high speed machining. Using a combination of process simulation and collision detection based on image analysis, a rapid detection approach is developed. The geometric model provides the cut geometry for the collision detection and records a dynamic geometric information for in-process workpiece. For the precise collision detection, a strategy of image analysis method is developed in order to make the approach efficient and maintian a high detection precision. An example of five-axis machining propeller is studied to demonstrate the proposed approach. It has shown that the collision detection task can be achieved with a near real-time performance.

scholarly journals Navigating by touch: haptic Monte Carlo localization via geometric sensing and terrain classification

2021 ◽  
Vol 45 (6) ◽  
pp. 843-857
Author(s):  
Russell Buchanan ◽  
Jakub Bednarek ◽  
Marco Camurri ◽  
Michał R. Nowicki ◽  
Krzysztof Walas ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Estimation Error ◽  
Extreme Environments ◽  
Legged Robot ◽  
Terrain Classification ◽  
Localization Algorithm ◽  
Geometric Information ◽  
Contact Points ◽  
Monte Carlo Localization ◽  
Geometric Sensing

AbstractLegged robot navigation in extreme environments can hinder the use of cameras and lidar due to darkness, air obfuscation or sensor damage, whereas proprioceptive sensing will continue to work reliably. In this paper, we propose a purely proprioceptive localization algorithm which fuses information from both geometry and terrain type to localize a legged robot within a prior map. First, a terrain classifier computes the probability that a foot has stepped on a particular terrain class from sensed foot forces. Then, a Monte Carlo-based estimator fuses this terrain probability with the geometric information of the foot contact points. Results demonstrate this approach operating online and onboard an ANYmal B300 quadruped robot traversing several terrain courses with different geometries and terrain types over more than 1.2 km. The method keeps pose estimation error below 20 cm using a prior map with trained network and using sensing only from the feet, leg joints and IMU.

A SysML-Based Modeling Language for Mechatronic System Architecture

2015 ◽  
Author(s):  
Ruirui Chen ◽  
Yusheng Liu ◽  
Yue Cao ◽  
Jing Xu
Keyword(s):  
Systems Engineering ◽  
System Architecture ◽  
Modeling Language ◽  
Mechatronic Systems ◽  
Geometric Information ◽  
Automatic Reasoning ◽  
Control Behavior ◽  
Reasoning System ◽  
And Control ◽  
Model Based Systems Engineering

Model Based Systems Engineering (MBSE) is the mainstream methodology for the design of complex mechatronic systems. It emphasizes the application of the system architecture, which highly depends on a formalized modeling language. However, such modeling language is less researched in previous studies. This paper proposes a general modeling language for representing the system architecture, aiming for representing function, physical effect, geometric information and control behavior which the system should satisfy. It facilitates the communication of designers from different technological domains and supports a series of applications such as automatic reasoning, system simulation, etc. The language is illustrated and verified with a practical mechatronic device finally.

scholarly journals Revealing the Mass Loss Structures of Four Key Massive Binaries Using Optical Spectropolarimetry

2014 ◽  
Vol 9 (S307) ◽  
pp. 336-341
Author(s):  
Jamie R. Lomax
Keyword(s):  
Mass Loss ◽  
Binary Systems ◽  
Hot Spot ◽  
Polarized Light ◽  
Opening Angle ◽  
Geometric Information ◽  
Intrinsic Polarization ◽  
Polarization Component ◽  
Circumstellar Material ◽  
Large Opening

AbstractThe majority of massive stars are members of binary systems. However, in order to understand their evolutionary pathways, mass and angular momentum loss from these systems needs to be well characterized. Self-consistent explanations for their behavior across many wavelength regimes need to be valid in order to illuminate key evolutionary phases. I present the results of linear spectropolarimetric studies of three key binaries (β Lyrae, V356 Sgr, V444 Cyg, and WR 140) which reveal important geometric information about their circumstellar material. β Lyrae exhibits a repeatable discrepancy between secondary eclipse in the total and polarized light curves that indicates an accretion hot spot has formed on the edge of the disk in the system. The existence of this hot spot and its relationship to bipolar outflows within the system is important in the understanding of mass transfer dynamics in Roche-lobe overflow binaries. Preliminary work on V356 Sgr suggests the system maybe surrounded by a common envelope. V444 Cyg shows evidence that its shock creates a cone with a large opening angle of missing material around the WN star. This suggests the effects of radiative inhibition or braking, can be significant contributors to the location and shape of the shock within colliding wind binaries. The intrinsic polarization component of WR 140 is likely due to the formation of dust within the system near periastron passages. Continued work on these and additional objects will provide new and important constraints on the mass loss structures within binary systems.

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