Colour tracking technique by using pixy CMUcam5 for wheelchair luggage follower

Ahmad, Muhammad Shakil; Rong, Hanxiao; Alhady, S. S. N.; Rahiman, Wan; Othman, W. A. F. W.

doi:10.1109/iccsce.2017.8284402

Cited by 11 publications

(5 citation statements)

References 8 publications

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“…Ketika bola berada pada posisi titik buta robot (titik dimana kamera tidak mendapatkan citra bola), robot harus berputar untuk mendeteksi posisi bola. Hal tersebut tidak efisien, karena robot menghabiskan banyak waktu untuk berputar mendeteksi posisi bola yang berada diluar field of view (FOV) kamera [3].…”

Section: Pendahuluanunclassified

Perancangan Omni Vision Camera sebagai Sistem Pendeteksi Objek untuk Robot Sepak Bola

Fuady

Hidayatullah

Hais

et al. 2022

JJEEE

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Robot adalah kumpulan perangkat elektronika terintegrasi yang dapat bergerak dengan kontrol manusia atau otomatis menggunakan program yang telah ditanamkan terlebih dahulu. Salah satu jenis robot yang banyak dikembangkan yaitu robot sepak bola beroda yang dirancang memiliki kemampuan mendeteksi, menggiring, dan menendang bola ke gawang lawan. Kemampuan penting yang harus dimiliki yaitu kemampuan robot mendeteksi posisi bola. Permasalahan yang dihadapi umumnya yaitu kamera hanya memiliki field of view (FOV) 73.98° pada jarak 1,5 meter sehingga ketika bola berada pada posisi titik buta robot, robot harus berputar untuk mendeteksi posisi bola. Untuk menghindari kehilangan citra bola, robot harus dibekali kemampuan penglihatan seluruh sisinya yaitu menggunakan omnidirectional camera, akan tetapi membutuhkan penyesuaian algoritma pada robot serta harganya relatif mahal sehingga tidak efektif. Sistem pendeteksi objek memanfaatkan omni vision camera yang menggunakan hyperbolic mirror yang diusulkan dapat mendeteksi objek di sekitar keliling robot. Omni vision camera mendeteksi objek secara realtime dengan metode color based filtering menggunakan algoritma Color Connected Components (CCC). Sistem pendeteksi objek menggunakan omni vision camera mampu mendeteksi objek secara 360° sudut visual robot ketika intensitas cahaya berada antara 60 hingga 210 lux. Kemampuan waktu pendeteksian lebih efisien dengan waktu rata-rata 6,33 detik lebih cepat dibandingkan dengan single camera vision yaitu 7,65 detik serta dapat mendeteksi objek bola dengan jarak terdekat 10 cm dan jarak terjauh 160 cm. Robot is integrated electronic devices that can move with human control or autonomous using a program that has been implanted in advance. One type of robot that has been widely developed is a wheeled soccer robot which is designed to have the ability to detect, dribble, and kick the ball into the opponent's goal. An important ability that must be possessed is the robot's ability to detect the position of the ball. The common problem is that the camera only has a field of view (FOV) of 73.98° at a distance of 1.5 meters, so that when the ball is in the robot's blind spot position, the robot must rotate to detect the ball's position. To avoid losing the object image, the robot must be equipped with the ability to see all sides, using an omnidirectional camera, but requires algorithm adjustments on the robot and the price is relatively expensive so it is not effective. An object detection system utilize omni vision camera that using hyperbolic mirror is proposed which can detect objects around the robot's circumference. Omni vision camera detects objects in real time with the color based filtering method using the Color Connected Components (CCC) algorithm. The object detection system using an omni vision camera is capable of detecting objects 360° from the robot's visual angle when the light intensity is between 60 to 210 lux. The ability of detection time is more efficient with an average time of 6.33 seconds faster than single camera vision, which is 7.65 seconds and can detect image of objects with the closest distance of 10 cm and the farthest distance of 160 cm.

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Section: Pendahuluanunclassified

Perancangan Omni Vision Camera sebagai Sistem Pendeteksi Objek untuk Robot Sepak Bola

Fuady

Hidayatullah

Hais

et al. 2022

JJEEE

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“…Image processing and obstacle detection system. [98] Pan-Tilt-Zoom (PTZ) c, gyroscope, encoder, laser, wheelchair.…”

Section: Control Systems Referencesmentioning

confidence: 99%

“…The chair moves by means of sensors placed on the ceiling so that it can make the journey. Other methods, such as that used by Ahmad et al [98] for the use of artificial vision in mobility using wheelchairs, describe a colour tracking technique. A system is developed by Wu et al [95] where multi-sensorial data is used to track a companion.…”

Section: Cameras or Optical Sensors With Different Characteristicsmentioning

confidence: 99%

Control Systems and Electronic Instrumentation Applied to Autonomy in Wheelchair Mobility: The State of the Art

Callejas-Cuervo

Gonźalez-Cely

Bastos

2020

Sensors

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Automatic wheelchairs have evolved in terms of instrumentation and control, solving the mobility problems of people with physical disabilities. With this work it is intended to establish the background of the instrumentation and control methods of automatic wheelchairs and prototypes, as well as a classification in each category. To this end a search of specialised databases was carried out for articles published between 2012 and 2019. Out of these, 97 documents were selected based on the inclusion and exclusion criteria. The following categories were proposed for these articles: (a) wheelchair instrumentation and control methods, among which there are systems that implement micro-electromechanical sensors (MEMS), surface electromyography (sEMG), electrooculography (EOG), electroencephalography (EEG), and voice recognition systems; (b) wheelchair instrumentation, among which are found obstacle detection systems, artificial vision (image and video), as well as navigation systems (GPS and GSM). The results found in this review tend towards the use of EEG signals, head movements, voice commands, and algorithms to avoid obstacles. The most used techniques involve the use of a classic control and thresholding to move the wheelchair. In addition, the discussion was mainly based on the characteristics of the user and the types of control. To conclude, the articles exhibited the existing limitations and possible solutions in their designs, as well as informing the physically disabled community about the technological developments in this field.

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“…CMUcam used as a tracking sensor contributed to a successful autonomous mobile robot. The taken value of camera's field of view (FOV) with several details from other sensors gathered as well to establish the robust tracking system [10][11][12][13].…”

Section: Mobile Robotmentioning

confidence: 99%

Embedded Artificial Neural Network FPGA Controlled Cart

Ahmad¹,

Alhady²,

Oon³

et al. 2019

Adv. sci. technol. eng. syst. j.

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An artificial neural network (ANN) computing system can be significantly influenced by its implementation type. The software implemented ANN can produce high accuracy output with slow computation time performance compared to hardware implemented ANN which runs at a faster computation time but with low accuracy. Normally, software implementation reduces the proficiency and efficiency of the model. Robot performance plays an important role as it needs fast response to process information that is applied with ANN. As a consequence, the proposed research focuses on comparison between hardware and software implementation multilayer perceptron (MLP) for cart follower in Field Programmable Logic Array (FPGA). Both of the software and hardware models produced the same precision where the output distance at angles-10°, 0° and 10° shows same percentage error. Besides that, both of the models have similar root mean square error (RMSE) which are 0.469, 0.479 and 0.267 at-10°, 0° and 10° respectively. The processing time of MLP model implemented in hardware and software are at 1.91μs and 78.06μs respectively. Thus, it can be concluded that hardware implementation is better than software implementation.

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Colour tracking technique by using pixy CMUcam5 for wheelchair luggage follower

Cited by 11 publications

References 8 publications

Perancangan Omni Vision Camera sebagai Sistem Pendeteksi Objek untuk Robot Sepak Bola

Perancangan Omni Vision Camera sebagai Sistem Pendeteksi Objek untuk Robot Sepak Bola

Control Systems and Electronic Instrumentation Applied to Autonomy in Wheelchair Mobility: The State of the Art

Embedded Artificial Neural Network FPGA Controlled Cart

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