Robot Navigation Model in a Multi-Target Domain Amidst Static and Dynamic Obstacles

2018 ◽  
Author(s):  
Michael K. Ayomoh ◽  
Oyindamola A Omotuyi ◽  
Adriaan J.G. Roux ◽  
Oluwole A Olufayo
Keyword(s):  
Robot Navigation ◽  
Target Domain

DEVELOPMENT OF A CONTROL STRATEGY FOR MOBILE ROBOT NAVIGATION IN UNKNOWN TERRAIN

2019 ◽  
Author(s):  
Diego Gabriel Gomes Rosa ◽  
Carlos Luiz Machado de souza junior ◽  
Marco Antonio Meggiolaro ◽  
Luiz Fernando Martha
Keyword(s):  
Mobile Robot ◽  
Control Strategy ◽  
Robot Navigation ◽  
Mobile Robot Navigation

Bounds on the partition dimension of convex polytopes

2020 ◽  
Vol 23 ◽  
Author(s):  
Jia-Bao Liu ◽  
Muhammad Faisal Nadeem ◽  
Mohammad Azeem
Keyword(s):  
Combinatorial Optimization ◽  
Computer Science ◽  
Facility Location ◽  
Robot Navigation ◽  
Convex Polytopes ◽  
Pharmaceutical Chemistry ◽  
Resolving Set ◽  
Minimum Number ◽  
Partition Dimension ◽  
Np Problem

Aims and Objective: The idea of partition and resolving sets plays an important role in various areas of engineering, chemistry and computer science such as robot navigation, facility location, pharmaceutical chemistry, combinatorial optimization, networking, and mastermind game. Method: In a graph to obtain the exact location of a required vertex which is unique from all the vertices, several vertices are selected this is called resolving set and its generalization is called resolving partition, where selected vertices are in the form of subsets. Minimum number of partitions of the vertices into sets is called partition dimension. Results: It was proved that determining the partition dimension a graph is nondeterministic polynomial time (NP) problem. In this article, we find the partition dimension of convex polytopes and provide their bounds. Conclusion: The major contribution of this article is that, due to the complexity of computing the exact partition dimension we provides the bounds and show that all the graphs discussed in results have partition dimension either less or equals to 4, but it cannot been be greater than 4.

The Concept of Animals in Balinese Proverbs

2017 ◽  
Vol 3 (1) ◽  
pp. 87
Author(s):  
I Wayan Budiarta ◽  
Ni Wayan Kasni
Keyword(s):  
Short Story ◽  
Cognitive Processes ◽  
Qualitative Data ◽  
Syntactic Structure ◽  
The Body ◽  
Biological Characteristic ◽  
Speech Community ◽  
Target Domain ◽  
Source Domain ◽  
Mapping Process

This research is aimed to figure out the syntactic structure of Balinese proverbs, the relation of meaning between the name of the animals and the meaning of the proverbs, and how the meanings are constructed in logical dimension. This research belongs to a qualitative as the data of this research are qualitative data which taken from a book entitled Basita Paribahasa written by Simpen (1993) and a book of Balinese short story written by Sewamara (1977). The analysis shows that the use of concept of animals in Balinese proverbs reveal similar characteristics, whether their form, their nature, and their condition. Moreover, the cognitive processes which happen in resulting the proverb is by conceptualizing the experience which is felt by the body, the nature, and the characteristic which owned by the target with the purpose of describing event or experience by the speech community of Balinese. Analogically, the similarity of characteristic in the form of shape of source domain can be proved visually, while the characteristic of the nature and the condition can be proved through bodily and empirical experiences. Ecolinguistics parameters are used to construct of Balinese proverbs which happen due to cross mapping process. It is caused by the presence of close characteristic or biological characteristic which is owned by the source domain and target domain, especially between Balinese with animal which then are verbally recorded and further patterned in ideological, biological, and sociological dimensions.

Real-time road edge following for mobile robot navigation

1990 ◽  
Vol 2 (1) ◽  
pp. 35 ◽  
Author(s):  
R.A. Lotufo ◽  
A.D. Morgan ◽  
E.L. Dagless ◽  
D.J. Milford ◽  
J.F. Morrissey ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Real Time ◽  
Robot Navigation ◽  
Mobile Robot Navigation

scholarly journals Power graphs and exchange property for resolving sets

2019 ◽  
Vol 17 (1) ◽  
pp. 1303-1309 ◽  
Author(s):  
Ghulam Abbas ◽  
Usman Ali ◽  
Mobeen Munir ◽  
Syed Ahtsham Ul Haq Bokhary ◽  
Shin Min Kang
Keyword(s):  
Present Article ◽  
Linear Algebra ◽  
Finite Groups ◽  
Robot Navigation ◽  
Simple Graph ◽  
Exchange Property ◽  
Metric Dimension ◽  
Sufficient Condition ◽  
Resolving Set ◽  
Dihedral Groups

Abstract Classical applications of resolving sets and metric dimension can be observed in robot navigation, networking and pharmacy. In the present article, a formula for computing the metric dimension of a simple graph wihtout singleton twins is given. A sufficient condition for the graph to have the exchange property for resolving sets is found. Consequently, every minimal resolving set in the graph forms a basis for a matriod in the context of independence defined by Boutin [Determining sets, resolving set and the exchange property, Graphs Combin., 2009, 25, 789-806]. Also, a new way to define a matroid on finite ground is deduced. It is proved that the matroid is strongly base orderable and hence satisfies the conjecture of White [An unique exchange property for bases, Linear Algebra Appl., 1980, 31, 81-91]. As an application, it is shown that the power graphs of some finite groups can define a matroid. Moreover, we also compute the metric dimension of the power graphs of dihedral groups.

scholarly journals THÖR: Human-Robot Navigation Data Collection and Accurate Motion Trajectories Dataset

2020 ◽  
Vol 5 (2) ◽  
pp. 676-682
Author(s):  
Andrey Rudenko ◽  
Tomasz P. Kucner ◽  
Chittaranjan S. Swaminathan ◽  
Ravi T. Chadalavada ◽  
Kai O. Arras ◽  
...  
Keyword(s):  
Data Collection ◽  
Robot Navigation ◽  
Motion Trajectories ◽  
Navigation Data

scholarly journals Path Planning and Replanning for Mobile Robot Navigation on 3D Terrain: An Approach Based on Geodesic

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Kun-Lin Wu ◽  
Ting-Jui Ho ◽  
Sean A. Huang ◽  
Kuo-Hui Lin ◽  
Yueh-Chen Lin ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Robot Navigation ◽  
Tangent Plane ◽  
Intersection Point ◽  
Mobile Robot Navigation ◽  
Complete Manifold ◽  
Geodesic Triangle ◽  
Planning Stage ◽  
3D Terrain ◽  
Bonnet Theorem

In this paper, mobile robot navigation on a 3D terrain with a single obstacle is addressed. The terrain is modelled as a smooth, complete manifold with well-defined tangent planes and the hazardous region is modelled as an enclosing circle with a hazard grade tuned radius representing the obstacle projected onto the terrain to allow efficient path-obstacle intersection checking. To resolve the intersections along the initial geodesic, by resorting to the geodesic ideas from differential geometry on surfaces and manifolds, we present a geodesic-based planning and replanning algorithm as a new method for obstacle avoidance on a 3D terrain without using boundary following on the obstacle surface. The replanning algorithm generates two new paths, each a composition of two geodesics, connected via critical points whose locations are found to be heavily relying on the exploration of the terrain via directional scanning on the tangent plane at the first intersection point of the initial geodesic with the circle. An advantage of this geodesic path replanning procedure is that traversability of terrain on which the detour path traverses could be explored based on the local Gauss-Bonnet Theorem of the geodesic triangle at the planning stage. A simulation demonstrates the practicality of the analytical geodesic replanning procedure for navigating a constant speed point robot on a 3D hill-like terrain.

Perception-action map learning in controlled multiscroll systems applied to robot navigation

2008 ◽  
Vol 18 (4) ◽  
pp. 043119 ◽  
Author(s):  
Paolo Arena ◽  
Sebastiano De Fiore ◽  
Luigi Fortuna ◽  
Luca Patané
Keyword(s):  
Robot Navigation ◽  
Map Learning ◽  
Perception Action
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