6-DOF PC-Based Robotic Arm (PC-ROBOARM) with efficient trajectory planning and speed control

Hao, Wong Guan; Leck, Yap Yee; Hun, Lim Chot

doi:10.1109/icom.2011.5937171

Cited by 29 publications

(5 citation statements)

References 9 publications

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“…The work expressed in [1][2][3] presented the approach towards the development of automated electro-mechanical manipulators. The various approaches are proposed for the step-by-step design and development of PC-based robotic arms having several degrees of freedom [4][5][6][7]. The technique of color segmentation for object detection in real-time vision-based applications which is implemented through a stereoscopic system is briefly portrayed in [8].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Object Detection and Localization for Vision-Based Robot Manipulator

Batra

Kumar

2021

SN COMPUT. SCI.

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Traditionally, the robot manipulators were assigned a monotonous task. Therefore, in an aim of simplifying the interactions between unstructured surrounding and robots, as well as to carry out the more complex operations, cognitive abilities such as visual perception are appended to systems for the sake of intelligent operations. Hence, this article directed towards the multistage process involved in the design and development of vision-based robot manipulator suitable for pick and place operation in real-time entailing external disturbances. The intact system development occurs in three phases: first, the robot manipulator with 3-DOF is designed, developed and also enhanced by integrating the vision source. Second, an algorithm for object detection and localization in real time is framed in which segmented object matrices are returned by the former and the position of the stabilized object is returned by the latter. Third, entire hardware-software integration is achieved to perform the desired operation. The algorithm developed in this paper proves to be good for the developed vision-based manipulator, as we achieve quite a good accuracy in object detection algorithm whereas 98.41-99.12% accuracy is achieved in the object localization algorithm. Keywords Object detection • Object localization • Real-time robot manipulatorThis article is part of the topical collection "Applications of Cloud Computing, Data Analytics and Building Secure Networks" guestedited by Rajnish Sharma, Pao-Ann Hsiung and Sagar Juneja".

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Section: Introductionmentioning

confidence: 99%

Real-Time Object Detection and Localization for Vision-Based Robot Manipulator

Batra

Kumar

2021

SN COMPUT. SCI.

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“…II. RELATED WORK Works related to rescue robot and application of robotic arm or manipulator with integration and analysis [7][8][9][10][11][12][13][14] are presented in a short manner. In 2005, in Japan, Yu-Huan Chiu, Naoji Shiroma, et al have researched for FUMA: Environment Information Gathering Wheeled Rescue Robot with One-DOF Arm for information collection purpose at disaster areas [7].…”

Section: Introductionmentioning

confidence: 99%

“…In 2016, Bin Li, Yangmin Li, et al prosed a novel over-constrained three degree-of-freedom (DOF) spatial parallel manipulator (SPM). The architecture of the SPM is comprised of a moving platform attached to a base through two revolute-prismatic-universal jointed serial linkages and one spherical-prismatic-revolute jointed serial linkage [13] and also in 2011, Wong Guan Hao, Yap Yee Leck, et al made a 6-DOF Pc-Based Robotic Arm (PC-ROBO ARM) with efficient Trajectory planning and speed control [14]. Some of the noble contribution to this rescue robot and robotic manipulator which are stated above describes and proposes only the degree of freedom integration.…”

Section: Introductionmentioning

confidence: 99%

Sigma-3: Integration and Analysis of a 6 DOF Robotic Arm Configuration in a Rescue Robot

Bindu¹,

Neloy²,

Alam³

et al. 2019

2019 4th International Conference on Robotics and Automation Engineering (ICRAE)

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This paper introduces a rescue robot named Sigma-3 which is developed for potential applications such as helping hands for humans where a human can't reach to have an assessment of the hazardous environment. Also, these kinds of robot can be controlled remotely with an adequate control system. The proposed methodology forces on two issues -1. Novel mechanism design for measuring rotation, joints, links of Degree of Freedom (DOF) for an arm which is integrated with Sigma-3 2. Precise measuring of end-effector motion control over three dimensions. In the proposed mechanism design, the DOF measurement is presented by a planar and spatial mechanism where 4 types of rigid joints build up each DOF with controlling by six High Torque MG996R servo motors. Rotation and DOF measurement are consisting of different theoretical references of Rotation Matrix, Inverse Kinematics with experimental results. Presented methodology over Oscillation Damping performance exhibits less than 3% error while configuring for on hands testing. Another evaluation of operating time state strongly defends the mechanism of low power consumption ability.

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“…Persamaan solusi invers memiliki karakteristik dimensi dan nonlinier yang tinggi, solusinya kompleks, dan sulit untuk menemukan solusi yang akurat. Solusi invers tradisional dapat secara kasar dibagi menjadi metode aljabar [1][2][3][4][5][6] dan metode geometris [7][8][9] sudah jarang digunakan karena hasil yang buruk. Dalam metode iteratif numerik yang lebih populer pada tahap ini [10][11][12][13], evolusi, bionik dan simulasi, jaringan saraf, dan algoritma lainnya adalah algoritma kecerdasan yang umum digunakan [14][15][16].…”

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Analisa Kesalahan Trajektori dan Algoritma Solusi Invers pada Robot Lengan Berdasarkan Jaringan QACA-RBF

Farouq¹,

Fani²,

Muhaimin³

2020

COMPLETE

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Dalam rangka meningkatkan akurasi posisi dan trajektori dari robot lengan UR5, algoritma solusi invers pada robot lengan berdasarkan jaringan QACA-RBF diajukan. Desain algoritma ini menggunakan model prediksi melalui jaringan saraf dan menggunakan algoritma koloni semut kuantum untuk mengoptimalkan bobot keluarannya. Dalam memecahkan masalah ini, algoritma koloni semut kuantum memiliki presisi konvergen yang rendah dan mudah jatuh ke dalam solusi local optimal dalam algoritma solusi invers dari derajat kebebasan pada robot lengan, maka peningkatan pengukuran seperti local optimasi dan batas maksimum minimum feromon dan variasi dibutuhkan. Dengan membandingkan hasil simulasi dari hasil simulasi robot lengan UR5 dan hasil simulasi berdasarkan jaringan saraf ACA, QACA, dan RBF untuk mendapatkan posisi dan gerak trajektori pada titik ruang dengan kepresisian disetiap algoritma. Dengan skema tersebut agar dapat membuktikan kelayakan algotirma jaringan QACA-RBF.

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6-DOF PC-Based Robotic Arm (PC-ROBOARM) with efficient trajectory planning and speed control

Cited by 29 publications

References 9 publications

Real-Time Object Detection and Localization for Vision-Based Robot Manipulator

Real-Time Object Detection and Localization for Vision-Based Robot Manipulator

Sigma-3: Integration and Analysis of a 6 DOF Robotic Arm Configuration in a Rescue Robot

Analisa Kesalahan Trajektori dan Algoritma Solusi Invers pada Robot Lengan Berdasarkan Jaringan QACA-RBF

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