Dynamic Object Recognition Using Precise Location Detection and ANN for Robot Manipulator

2017 ◽  
Author(s):  
Kyekyung Kim ◽  
Jaemin Cho ◽  
Jihyeong Pyo ◽  
Sangseung Kang ◽  
Jinho Kim
Keyword(s):  
Object Recognition ◽  
Robot Manipulator ◽  
Dynamic Object ◽  
Precise Location ◽  
Location Detection

scholarly journals Facilitation by view combination and coherent motion in dynamic object recognition

2010 ◽  
Vol 50 (2) ◽  
pp. 202-210 ◽  
Author(s):  
Alinda Friedman ◽  
Quoc C. Vuong ◽  
Marcia Spetch
Keyword(s):  
Object Recognition ◽  
Coherent Motion ◽  
Dynamic Object

scholarly journals A 320 mW 342 GOPS Real-Time Dynamic Object Recognition Processor for HD 720p Video Streams

2013 ◽  
Vol 48 (1) ◽  
pp. 33-45 ◽  
Author(s):  
Jinwook Oh ◽  
Gyeonghoon Kim ◽  
Junyoung Park ◽  
Injoon Hong ◽  
Seungjin Lee ◽  
...  
Keyword(s):  
Object Recognition ◽  
Real Time ◽  
Dynamic Object ◽  
Video Streams ◽  
Time Dynamic

scholarly journals Dynamic object recognition in pigeons and humans

2006 ◽  
Vol 34 (3) ◽  
pp. 215-228 ◽  
Author(s):  
Marcia L. Spetch ◽  
Alinda Friedman ◽  
Quoc C. Vuong
Keyword(s):  
Object Recognition ◽  
Dynamic Object

Pick-place of dynamic objects by robot manipulator based on deep learning and easy user interface teaching systems

2017 ◽  
Vol 44 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Delowar Hossain ◽  
Genci Capi ◽  
Mitsuru Jindai ◽  
Shin-ichiro Kaneko
Keyword(s):  
Object Recognition ◽  
Real Time ◽  
Target Location ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Content Type ◽  
Intermediate Layers ◽  
Object Features ◽  
Short Time ◽  
Assembly Tasks

Purpose Development of autonomous robot manipulator for human-robot assembly tasks is a key component to reach high effectiveness. In such tasks, the robot real-time object recognition is crucial. In addition, the need for simple and safe teaching techniques need to be considered, because: small size robot manipulators’ presence in everyday life environments is increasing requiring non-expert operators to teach the robot; and in small size applications, the operator has to teach several different motions in a short time. Design/methodology/approach For object recognition, the authors propose a deep belief neural network (DBNN)-based approach. The captured camera image is used as the input of the DBNN. The DBNN extracts the object features in the intermediate layers. In addition, the authors developed three teaching systems which utilize iPhone; haptic; and Kinect devices. Findings The object recognition by DBNN is robust for real-time applications. The robot picks up the object required by the user and places it in the target location. Three developed teaching systems are easy to use by non-experienced subjects, and they show different performance in terms of time to complete the task and accuracy. Practical implications The proposed method can ease the use of robot manipulators helping non-experienced users completing different assembly tasks. Originality/value This work applies DBNN for object recognition and three intuitive systems for teaching robot manipulators.

scholarly journals Precise Fault Location Detection Using IOT

2021 ◽  
pp. 74-79
Author(s):  
Prof. Sayyad Naimuddin ◽  
Prof. Nahid Khan ◽  
Vaishali Gupta ◽  
Tuba Farhat ◽  
Deepak Singh Mujeebuddin Ansari ◽  
...  
Keyword(s):  
Transmission Lines ◽  
Power Dissipation ◽  
Fault Location ◽  
Electrical Power ◽  
Precise Location ◽  
Human Errors ◽  
Location Detection ◽  
Short Circuits ◽  
To Come ◽  
Transmission And Distribution

Transmission and distribution lines are used to transmit and distribute electrical power throughout load center. The problem with these lines are, because the loads are unbalanced and their attraction towards various faults as a results of lightning, short circuits, faulty equipment’s, miss-operation, human errors, overload, and aging. To avoid this case and that we need the precise location of fault occurrence. To avoid this situation, we need the exact location of fault occurrence. This problem is handled by a set of resistors representing cable length in KMs and fault creation is made by a set of switches at every known KM to cross check the accuracy of the same. Only way to solve this problem is to come up with a mechanism that can detect the fault in an electricity transmission line automatically and intimate the authorities with a precise location. Through this project we develop a device that uses sensors to sense the incoming & outgoing values and detect healthy and faulty condition. And, the system will be integrated with IoT mechanism, to intimate the responsible people real time with the location information. Moreover technical losses occur naturally and are caused because of power dissipation in transmission lines, transformers, and other equipments. The system prevents the illegal usage of electricity.

scholarly journals Identify Occurrence of Substance Object of a Certain Classification in Fractional Videos and Pictures

2020 ◽  
Vol 9 (3) ◽  
pp. 3728-3731
Keyword(s):  
Computer Vision ◽  
Online Learning ◽  
Object Recognition ◽  
Object Detection ◽  
New Method ◽  
Learning Method ◽  
Dynamic Object ◽  
Geometric Shapes ◽  
New Learning ◽  
Detection And Recognition

Object detection and recognition are the meta-heuristic problems in computer vision. Practically usable dynamic object recognition methods are still unavailable. A new method was proposed which improves over existing methods in every stage. In that addition features like geometric shapes, ellipsis are added. An heuristic codebook was proposed of good generalization and discriminative properties, enabling multipath interferences mechanisms on propagation of1 conditional livelihood. A new learning method also proposed which is capable of online learning

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