Gesture Control Menggunakan IMU MPU 6050 Metode Kalman Filter Sebagai Kendali Quadcopter

Tugas pokok TNI AU yaitu menegakkan kedaulatan diwilayah Indonesia maka diperlukan sumber daya manusia yang berkemampuan alutsista sesuai perkembangan ilmu dan teknologi. Ssalah satu teknologi pesawat tanpa awak sangat penting maka penelitian diharapkan berkembangan sistem kendali drone dengan gesture, sistem komunikasi dari radio ke wireless dan peningkatan akurasi sensor gyroscope dengan alogaritma Kalman filter. Sistem dibangun dengan menggunakan drone quadcopter Dji tello dengan sensor gyroscope menggunakan IMU MPU 6050 dan sistem pengolah mengunakan Arduino Uno menggunakan software Sketch Arduino untuk kalman filter serta komunikasi wireless dengan Python. Sistem dapat mengendalikan drone dengan gesture pada operasi take off pada susdut 60 sampai 90 sudut pitch, untuk landing pada sudut -60 sampai -90, untuk 362 pengambilan data pada metode kalman filter variasi minamal 0,00166 dan variasi 0.00564 pada range 89.25 sampai 89.30. untuk roll dengan cara gesture kekanan jika lebih 30 sampai 90 dan gesture kekiri jika lebih -30 sampai -90 dengan varian minimal 0.0456 dan varial 0.0141 pada sudut 90.42 sampai 90.44 dari percobaan 362 sampel data, sistem dapat komunikasi dengan sistem Wireless.

Comparison of Xbox One and Steam Joystick-based Operating System User Interface using KLM- GOMS

Despite having many advances in video game control such as voice or gesture control, most video game console manufacturers still use a joystick as the main control for their console. Currently, the problem with video game manufacturers is that instead of using the joystick as the point of user interface design, they instead used a design from another device such as a computer or tv. The research will compare Xbox One and Steam OS user interface by using KLM-GOMS Model. Based on the calculation it is concluded that the overall Xbox One has a more efficient design compared to Steam.

Architecture Design and VLSI Implementation of 3D Hand Gesture Recognition System

With advancements in technology, more and more research is being focused on enhancing daily life quality and convenience. Along with the increase in the development of gesture control systems, many controllers, such as the keyboard, mouse, and other devices, have been replaced with remote control products, which are gradually becoming more intuitive for users. However, vision-based hand gesture recognition systems still have many problems to overcome. Most hand detection methods adopt a skin filter or motion filter for pre-processing. However, in a noisy environment, it is not easy to correctly extract interesting objects. In this paper, a VLSI design with dual-cameras has been proposed to construct a depth map with a stereo matching algorithm and recognize hand gestures. The proposed system adopts an adaptive depth filter to separate interesting foreground objects from the background. We also propose dynamic gesture recognition using depth and coordinate information. The system can perform static and dynamic gesture recognition. The ASIC design is implemented in TSMC 90 nm with about 47.3 K gate counts, and 27.8 mW of power consumption. The average accuracy of each gesture recognition is 83.98%.

Home Automation Berbasis Gesture Control Menggunakan Motion Processing Unit

Home automation dengan pengenalan isyarat gerakan tangan dapat memberi kemudahan kepada pemilik rumah untuk mengontrol peralatan elektronik rumahnya terutama kepada para penyandang disabilitas yang memiliki keterbatasan untuk berjalan. Pada penelitian sebelumnya, perangkat pembaca isyarat berupa sarung tangan yang dilengkapi sensor akselerometer dan giroskop. Perangkat tersebut kurang fleksibel saat digunakan untuk melakukan aktivitas lain secara bersamaan sehingga dibutuhkan perangkat yang lebih wearable. Penelitian ini mengembangkan home automation system dengan pengenalan isyarat gerakan tangan menggunakan Motion Processing Unit (MPU). Perangkat dibuat dalam bentuk jam tangan digital sehingga lebih praktis saat digunakan. Sensor MPU akan mendeteksi isyarat gerakan tangan dimana setiap isyarat gerakan diproses oleh Arduino Nano dan didefinisikan sebagai suatu perintah yang akan dikirim ke perangkat penerima melalui modul radio frekuensi. Setelah diuji perangkat yang dibuat dapat mengontrol peralatan elektronik rumah dengan isyarat gerakan tangan sesuai spesifikasi yang diinginkan dengan nilai error sebesar 2,5%. Sedangkan jarak maksimum perangkat pemancar yang masih dapat direspon oleh penerima adalah 10 m tanpa penghalang.

Influences of Gesture-Based Mobile Phone Use While Driving

The use of mobile phones while driving has been a hot topic in the field of driving safety for decades. Although there are few studies on the influence of gesture control on in-vehicle secondary tasks, this study aims to investigate the impact of gesture-based mobile phone use without touching while driving from the perspective of multiple-resource workload owing to visual, auditory, cognitive, and psychomotor resource occupation. A novel gesture control technique was adopted for secondary task interactions, to recognize the gestures of drivers. An experiment was conducted to study the influences of two interaction modes, traditional touch-based mobile phone interaction and gesture-based mobile phone interaction, on driving behavior in three different cognitive level task groups. The results indicate that gesture-based mobile phone interaction can improve driving performance with regard to lateral position-keeping ability and steering wheel control; nevertheless, it has no significant impact on longitudinal metrics such as driving speed, driving speed variation, and throttle control variation. Gesture-based mobile phone interactions have a larger effect on secondary tasks with medium cognitive load but not on actual operation tasks. It was also verified that the performance of gesture-based mobile phone interaction was better in secondary mobile phone tasks such as switching (e.g., switching songs) and adjusting (e.g., adjusting volume) than the traditional interaction mode. This study provides the theoretical and experimental support for human–computer interaction using gesture-based mobile phone interactive control in future automobiles.

Hand Gesture Based Touch-Free User Interface for Elevator/Lift

The user interfaces of control panels used for electronic automation have been limited to devices such as remote control, key pad and touch screen for a long time. These interfaces are not natural and nor flexible for users. Consumers are expecting natural efficient user interfaces. Recent improvements in sensor technology are now opening the path for developers to add gesture control to their products. This Project presents a switch control panel for Touch-free user interface using simple hand gestures technique to control operations of Elevator/Lift. This gesture-based switch control panel is not just limited to Elevator/Lift, but can also be implemented in other areas such as Vending machines, ATMs and many more with little changes in software & hardware if required. To use this interactive system based on hand gestures, one does not require any prerequisite knowledge as in the case of touch-screens, keyboard etc.