A graph search algorithm for delphinid whistle contours.

2009 ◽  
Vol 125 (4) ◽  
pp. 2737-2737
Author(s):  
Marie A. Roch ◽  
Bhavesh Patel ◽  
Melissa S. Soldevilla ◽  
John A. Hildebrand
Keyword(s):  
Search Algorithm ◽  
Graph Search

Optimal Robotic Assembly Planning Using Dijkstra’s Algorithm

1994 ◽  
Author(s):  
Sam Anand ◽  
Mohamed Sabri
Keyword(s):  
Configuration Space ◽  
Material Handling ◽  
Search Algorithm ◽  
Robotic Manipulators ◽  
Robotic Assembly ◽  
Graph Search ◽  
Assembly Planning ◽  
Robotic Welding ◽  
Fast Collision ◽  
Space Approach

Abstract Robots play an important role in the modern factory and are used in a manufacturing cell for several functions such as assembly, material handling, robotic welding, etc. One of the principal problems faced by robots while performing their tasks is the presence of obstacles such as fixtures, tools, and objects in the robot workspace. Such objects could result in a collision with one of the arms of the robots. Fast collision-free motion planning algorithms are therefore necessary for robotic manipulators to operate in a wide variety of changing environments. The configuration space approach is one of the widely used methods for collision-free robotic path planning. This paper presents a novel graph-based method of searching the configuration space for a collision-free path in a robotic assembly operation. Dijkstra’s graph search algorithm is used for optimizing the joint displacements of the robot while performing the assembly task. The methodology is illustrated using a simple robotic assembly planning task.

scholarly journals Learning Descriptors Invariance through Equivalence Relations within Manifold: A New Approach to Expression Invariant 3D Face Recognition

2020 ◽  
Vol 6 (11) ◽  
pp. 112
Author(s):  
Faisal R. Al-Osaimi
Keyword(s):  
Search Algorithm ◽  
Recognition Performance ◽  
Feature Space ◽  
Training Data ◽  
Equivalence Relations ◽  
Graph Search ◽  
Search Problem ◽  
New Approach ◽  
Unique Approach ◽  
Training Examples

This paper presents a unique approach for the dichotomy between useful and adverse variations of key-point descriptors, namely the identity and the expression variations in the descriptor (feature) space. The descriptors variations are learned from training examples. Based on labels of the training data, the equivalence relations among the descriptors are established. Both types of descriptor variations are represented by a graph embedded in the descriptor manifold. Invariant recognition is then conducted as a graph search problem. A heuristic graph search algorithm suitable for the recognition under this setup was devised. The proposed approach was tested on the FRGC v2.0, the Bosphorus and the 3D TEC datasets. It has shown to enhance the recognition performance, under expression variations, by considerable margins.

An Efficient Graph-Search Algorithm for Full Link Application Suggestion

2018 ◽  
pp. 536-545
Author(s):  
Haijie Zhang ◽  
Nan Zeng ◽  
Hu Song ◽  
Menghan Xu ◽  
Huiyu Wang ◽  
...  
Keyword(s):  
Search Algorithm ◽  
Graph Search

scholarly journals A graph search algorithm for indoor pursuit/evasion

2009 ◽  
Vol 50 (9-10) ◽  
pp. 1305-1317 ◽  
Author(s):  
Athanasios Kehagias ◽  
Geoffrey Hollinger ◽  
Sanjiv Singh
Keyword(s):  
Search Algorithm ◽  
Graph Search ◽  
Pursuit Evasion
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