scholarly journals Smoothing the Curvature of Trajectory of Ground Robot in 3D Space

2021 ◽  
Vol 24 (4) ◽  
pp. 107-125
Author(s):  
K. S. Zakharov ◽  
A. I. Saveliev
Keyword(s):  
Averaging Method ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Experimental Comparison ◽  
Rough Terrain ◽  
Smoothing Algorithm ◽  
A Algorithm ◽  
3D Space ◽  
Curve Smoothing ◽  
Three Dimensional Space

Purpose or research. Development of an algorithm for smoothing the trajectory of a ground robot over rough terrain, represented as a graph in three-dimensional space. Methods. This article presents the CSA (Curve Smoothing and Averaging) algorithm for smoothing local curves in the Oxy plane that make up a global curve, represented as a path on a connected graph in 3D space. The presented algorithm is based on the previously developed LRLHD-A * approach, which uses information about the vertices of the graph, their neighbors and the edges connecting them to select the area through which the smoothed curve will run. In order to avoid a broken curve at the output of the algorithm, a curve averaging method was developed, the idea of which is to shift the midpoints of local curves along the edges on which they are located. Results. An experimental comparison was made of the curvature of the trajectories obtained using the curve smoothing algorithm with curve averaging (CSA) and without it (CS). The method was carried out on a threedimensional map of the area, presented in the form of a graph with 100082 vertices. For the experiments, a sample of 10 pairs of random vertices was used, between which a path was built using the LRLHD-A * algorithm. The results of the experiments have shown that averaging the curve after smoothing reduces its curvature from 24 to 42%. Conclusion. Trajectories smoothed using the developed CSA algorithm have smoother curve bends at turns, compared to the algorithm taken as a basis. This allows the robots to move more smoothly and, as a consequence, reduce the consumption of the robot's battery.

Visional Attentional Allocation of Top-down and Bottom-up Cues in Three-Dimensional Space

2011 ◽  
Vol 179-180 ◽  
pp. 1322-1326
Author(s):  
Ru Ting Xia
Keyword(s):  
Visual Attention ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Depth Information ◽  
Top Down ◽  
Bottom Up ◽  
Attentional Allocation ◽  
3D Space ◽  
Target Locations ◽  
Three Dimensional Space

The aim of the present experiment was to investigate visual attentional allocation of top-down and bottom-up cues in three-dimensional (3D) space. Near and far stimuli were used by a 3D attention measurement apparatus. Two experiments were conducted in order to examine top-down and bottom-up controls of visual attention. In the experiment 1, the cue about the location of a target by means of location information. In the experiment 2, color cue by brief change of color at target locations was presented. Observers were required to judge whether the target presented nearer than fixation point or further than it. The results in experiment 1 and experiment 2 show that both location and color cue have the effect on reaction time, and that shift of attention were faster from far to near than the reverse. These findings suggest that (1) attention in 3D space might be operated with both location and color controls included the depth information, (2) the shift of visual attention in 3D space has an asymmetric characteristic in depth.

scholarly journals Cloth Simulation with Adaptive Force Model in Three-Dimensional Space

2018 ◽  
Vol 13 (1) ◽  
pp. 155892501801300
Author(s):  
Xuan Luo ◽  
Gaoming Jiang ◽  
Honglian Cong ◽  
Yan Zhao
Keyword(s):  
Human Body ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Mathematical Expression ◽  
Experimental Results ◽  
Force Model ◽  
Mathematical Form ◽  
Cloth Simulation ◽  
3D Space ◽  
Three Dimensional Space

An adaptive force model is proposed to achieve better performance between the accuracy and the speed of cloth simulation in three-dimensional (3D) space. The proposed force model can be expressed with a general mathematical form demonstrated by the distance between the clothing and the human body. This paper defines how a continuous adaptive area can be established with a shape “block”. It is clarified that, within a specific block, a force model is expressed with the gravity of the clothing, the forces of the adjacent blocks and the anti-force of the human body to the block. In this manner, the force model of the desired clothing can be obtained through a general mathematical expression. The simulations and experimental results demonstrate that the acceptable clothing simulation in 3D space can be achieved with higher speed by saving about 20.2% runtime, and the efficiency of the proposed scheme can be verified.

Spatial Inhibition of Return Affected by Self-Prioritization Effect in Three-Dimensional Space

Perception ◽  
2021 ◽  
Vol 50 (3) ◽  
pp. 231-248
Author(s):  
Xiaoyuan Liu ◽  
Qinyue Qian ◽  
Lingyun Wang ◽  
Aijun Wang ◽  
Ming Zhang
Keyword(s):  
Inhibition Of Return ◽  
Dimensional Space ◽  
Three Dimensional ◽  
The Self ◽  
Matching Task ◽  
Two Dimensional ◽  
Best Friends ◽  
Near Space ◽  
3D Space ◽  
Three Dimensional Space

Spatial inhibition of return (IOR) being affected by the self-prioritization effect (SPE) in a two-dimensional plane has been well documented. However, it remains unknown how the spatial IOR interacts with the SPE in three-dimensional (3D) space. By constructing a virtual 3D environment, Posner’s classically two-dimensional cue-target paradigm was applied to a 3D space. Participants first associated labels for themselves, their best friends, and strangers with geometric shapes in a shape-label matching task, then performed Experiment 1 (referential information appeared as the cue label) and Experiment 2 (referential information appeared as the target label) to investigate whether the IOR effect could be influenced by the SPE in 3D space. This study showed that when the cue was temporarily established with a self-referential shape and appeared in far space, the IOR effect was the smallest. When the target was temporarily established with a self-referential shape and appeared in near space, the IOR effect disappeared. This study suggests that the IOR effect was affected by the SPE when attention was oriented or reoriented in 3D space and that the IOR effect disappeared or decreased when affected by the SPE in 3D space.

scholarly journals A Hierarchical Anti-Hebbian Network Model for the Formation of Spatial Cells in Three-Dimensional Space

2018 ◽  
Author(s):  
Karthik Soman ◽  
Srinivasa Chakravarthy ◽  
Michael M. Yartsev
Keyword(s):  
Network Model ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Grid Cell ◽  
Cognitive Maps ◽  
3D Space ◽  
Learning Rules ◽  
Higher Dimensional ◽  
New Type ◽  
Three Dimensional Space

AbstractThree dimensional (3D) spatial cells in the mammalian hippocampalformationare believed to support the existence of 3D cognitive maps. Modeling studies are crucial to comprehend the neural principles governing the formation of these maps, yet to date very few have addressed this topic in 3D space. Here, we present a hierarchical network model for the formation of 3D spatial cells using anti-hebbian network. Built on empirical data, the model accounts for the natural emergence of 3D place, border and grid-cells as well as a new type of previously undescribed spatial cell type which we call plane cells. It further explains the plausible reason behind the place and grid-cell anisotropic coding that has been observed in rodents and the potential discrepancy with the predicted periodic coding during 3D volumetric navigation. Lastly, it provides evidence for the importance of unsupervised learning rules in guiding the formation of higher dimensional cognitive maps.

Extension of the Spatial PDI Model to Three Dimensions

1997 ◽  
Vol 84 (1) ◽  
pp. 176-178
Author(s):  
Frank O'Brien
Keyword(s):  
Population Density ◽  
Dimensional Space ◽  
Finite Lattice ◽  
Three Dimensional ◽  
Upper Bounds ◽  
Three Dimensions ◽  
Lower And Upper Bounds ◽  
Density Index ◽  
Three Dimensional Space

The author's population density index ( PDI) model is extended to three-dimensional distributions. A derived formula is presented that allows for the calculation of the lower and upper bounds of density in three-dimensional space for any finite lattice.

A Peptoid with Extended Shape in Water

2019 ◽  
Author(s):  
Jumpei Morimoto ◽  
Yasuhiro Fukuda ◽  
Takumu Watanabe ◽  
Daisuke Kuroda ◽  
Kouhei Tsumoto ◽  
...  
Keyword(s):  
Spectroscopic Analysis ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Biomolecular Recognition ◽  
Biological Application ◽  
New Class ◽  
Proteolytic Resistance ◽  
Pharmacokinetic Properties ◽  
Optically Pure ◽  
Three Dimensional Space

<div> <div> <div> <p>“Peptoids” was proposed, over decades ago, as a term describing analogs of peptides that exhibit better physicochemical and pharmacokinetic properties than peptides. Oligo-(N-substituted glycines) (oligo-NSG) was previously proposed as a peptoid due to its high proteolytic resistance and membrane permeability. However, oligo-NSG is conformationally flexible and is difficult to achieve a defined shape in water. This conformational flexibility is severely limiting biological application of oligo-NSG. Here, we propose oligo-(N-substituted alanines) (oligo-NSA) as a new peptoid that forms a defined shape in water. A synthetic method established in this study enabled the first isolation and conformational study of optically pure oligo-NSA. Computational simulations, crystallographic studies and spectroscopic analysis demonstrated the well-defined extended shape of oligo-NSA realized by backbone steric effects. The new class of peptoid achieves the constrained conformation without any assistance of N-substituents and serves as an ideal scaffold for displaying functional groups in well-defined three-dimensional space, which leads to effective biomolecular recognition. </p> </div> </div> </div>

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