Investigation of Using ANN and Stereovision in Delta Robot for Pick and Place Applications

Youssef, Abdelrahman; Bayoumy, Amgad; Atia, Mostafa R. A.

doi:10.18280/mmep.080502

Search citation statements

Order By: Relevance

Paper Sections

Select...

Description Of the Control System1

Kinematic Modeling Of the Robot1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The entire structure of the system [1][2][3][4][5] can be divided into three parts. The first part is the user control systems [6][7][8].…”

Section: Description Of the Control Systemmentioning

confidence: 99%

Development of an automated lighting control system in agricultural premises to save energy resources

Zakozhurnikov,

Gorshunova,

Pronina

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…The entire structure of the system [1][2][3][4][5] can be divided into three parts. The first part is the user control systems [6][7][8].…”

Section: Description Of the Control Systemmentioning

confidence: 99%

Development of an automated lighting control system in agricultural premises to save energy resources

Zakozhurnikov,

Gorshunova,

Pronina

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…The robot has 6 degrees of freedom and the camera is attached to its end-effector. The forward geometric model of the robot [11] is calculated by using Craig notation [12][13][14]. The transformations between the two successive links are calculated by using the Denavit-Hartenberg notation (Table 1).…”

Section: Kinematic Modeling Of the Robotmentioning

confidence: 99%

LSTM-Based Visual Control for Complex Robot Interactions

Djelal,

Ouanane,

Bouriachi

2023

JESA

View full text Add to dashboard Cite

This paper introduces a novel application of the Long Short-Term Memory (LSTM) recurrent neural network for the identification and control of complex systems. The computation-intensive task of calculating the interaction matrix, a necessity for visual control laws in these systems, makes LSTM a fitting solution. The proposed control law unfolds in two phases: an offline phase, where the LSTM is trained on a set of visual features to generate a kinematic screw vector, and an online phase, where the trained LSTM is utilized for real-time system control. To assess the efficacy of the LSTM-based approach, we undertook a case study involving a manipulator robot, the UR5. We executed a series of simulations under various conditions to illustrate the effectiveness of the proposed LSTM-based control law. The outcomes from these experiments affirm the robustness of the LSTM controller, outperforming traditional methods even when faced with rapid fluctuations in visual features, partial loss of visual information, and model uncertainties in the robot.

show abstract

Investigation of Using ANN and Stereovision in Delta Robot for Pick and Place Applications

Cited by 2 publications

References 12 publications

Development of an automated lighting control system in agricultural premises to save energy resources

Development of an automated lighting control system in agricultural premises to save energy resources

LSTM-Based Visual Control for Complex Robot Interactions

Contact Info

Product

Resources

About