Particle swarm optimization for coconut detection in a coconut tree plucking robot

Junaedy, Alfin; Sulistijono, Indra Adji; Hanafi, Nofria

doi:10.1109/kcic.2017.8228584

Cited by 8 publications

(4 citation statements)

References 5 publications

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“…But, machines equipped with a camera work on an automated machine by taking realtime decisions during coconut harvesting. An automated harvester machine has an on-board intelligence to identify coconut on a tree by means of digital image processing technology and an intelligent decision support system [12,16,17]. The coordinates of the identified coconuts are used by the microcontroller to guide the robotic arm while harvesting [13].…”

Section: Vision Unitmentioning

confidence: 99%

“…Coconut bunches were identified by supervised machine learning algorithms using K-means clustering and the SVM classifier is used [12]. The applicability of the image processing and particle swarm optimization (PSO) method to find the position of the coconut is described [16]. The use of the steady-state genetic algorithm to detect the coconut and harvest it by using an extendable arm equipped with a cutter is reported/claimed [17].…”

Section: Vision Unitmentioning

confidence: 99%

See 1 more Smart Citation

Status and Scope of Automated Coconut Harvester in India: A Review

Kumar

Bej

Pandey

2023

JEAI

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Coconut plays a substantial role in the Indian economy. South Indian states, namely Kerala, Karnataka, Tamil Nadu, and Andhra Pradesh are the leading producers accounting for more than 90% of the total coconut produced in the country. The traditional/conventional process of coconut harvesting includes climbing on the tree and cutting the coconut bunches with a cutter, which involves high risk. Climbing on a coconut tree is the main risk factor and it is life-threatening. The present review paper presents the status and future research need for automated coconut harvesting machines in India. The maximum speed or climbing with remote controlled coconut harvester was reported 0.055 ms-1. This paper also focuses on the basic components of the automated coconut harvesting machine, as well as the advantages and disadvantages of each component are critically analyzed based on its findings, future research needs are proposed in order to meet all the fundamental aspects of autonomous coconut harvesting machines.

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Section: Vision Unitmentioning

confidence: 99%

Section: Vision Unitmentioning

confidence: 99%

Status and Scope of Automated Coconut Harvester in India: A Review

Kumar

Bej

Pandey

2023

JEAI

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“…Untuk dapat melakukan proses autodocking, robot terlebih dahulu harus dapat mencari tempat docking station terdekat. Selain itu, robot membutuhkan pemandu agar dapat menuju ke tempat docking station terdekat dengan tepat dan aman.Penelitian yang dilakukan oleh Alfin Junaedy, dkk (2017) [14] dapat dijadikan salah satu referensi. Pada penelitian tersebut, digunakan metode particle swarm optimization (PSO) pada proses image processing untuk mendeteksi sebuah benda.…”

Section: Pendahuluanunclassified

Pencarian Jalur Terpendek Dalam Proses Autodocking Pada Mobile Robot Menggunakan Artificial Bee Colony

Rifandi

Sulistijono

Kuswadi

2019

Self Cite

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Proses autodocking pada mobile robot merupakan sebuah kemampuan tambahan yang dapat dimiliki oleh sebuah robot. Untuk dapat melakukan proses tersebut, robot terlebih dahulu harus dapat mencari tempat docking station terdekat. Selain itu, robot membutuhkan pemandu agar dapat menuju ke docking station terdekat dengan tepat dan aman. Untuk mendapatkan jalur terdekat, dibutuhkan posisi terakhir robot saat mendeteksi baterai dalam keadaan akan habis. Posisi robot tersebut sebagai masukan bagi artificial bee colony untuk menghasilkan jalur terdekat yang dapat memandu robot menuju docking station terdekat. Artificial bee colony digunakan sebagai optimasi pencarian tempat docking station yang jarak tempuhnya terdekat atau terpendek dari posisi robot serta aman dari halangan atau obstacle. Dari hasil percobaan, metode artificial bee colony mampu untuk mendapatkan jalur terpendek menuju lokasi docking station serta jalur yang didapatkan juga aman dari halangan. Jumlah populasi lebah yang digunakan sangat mempengaruhi jarak terdekat yang didapatkan oleh metode artificial bee colony. Semakin banyak populasi yang digunakan, maka semakin dekat jarak yang didapatkan oleh metode artificial bee colony. Jumlah iterasi juga mempengaruhi jarak terdekat yang didapatkan oleh artificial bee colony. Semakin banyak jumlah iterasi yang digunakan, maka semakin dekat jarak yang didapatkan meskipun jumlah populasi yang digunakan sama.

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“…In Industrial Engineering, examination timetabling problems [17], traveling salesman problem [18], and job-shop scheduling problems [19] are solved with PSO. In Robotics, particle swarm optimization in coconut tree plucking robot is introduced [20], and path planning problem is solved with PSO [21]. In these studies, it has been proven PSO success in point of both performance and speed in most of the studies.…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

Introductory Chapter: Swarm Intelligence and Particle Swarm Optimization

Erdoğmuş¹

2018

Particle Swarm Optimization With Applications

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Particle swarm optimization for coconut detection in a coconut tree plucking robot

Cited by 8 publications

References 5 publications

Status and Scope of Automated Coconut Harvester in India: A Review

Status and Scope of Automated Coconut Harvester in India: A Review

Pencarian Jalur Terpendek Dalam Proses Autodocking Pada Mobile Robot Menggunakan Artificial Bee Colony

Introductory Chapter: Swarm Intelligence and Particle Swarm Optimization

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