Lokalisasi Mobile Robot berdasarkan Citra Kamera OMNI menggunakan Fitur Surf

Deteksi lokasi diri atau lokalisasi diri adalah salah satu kemampuan yang harus dimiliki oleh mobile robot. Kemampuan lokalisasi diri digunakan untuk menentukan posisi robot di suatu daerah dan sebagai referensi untuk menentukan arah perjalanan selanjutnya. Dalam penelitian ini, lokalisasi robot didasarkan pada data citra yang ditangkap oleh kamera omnidirectional tipe catadioptric. Jumlah fitur terdekat antara citra 360o yang ditangkap oleh kamera Omni dan citra referensi menjadi dasar untuk menentukan prediksi lokasi. Ekstraksi fitur gambar menggunakan metode Speeded-Up Robust Features (SURF). Kontribusi pertama dari penelitian ini adalah optimasi akurasi deteksi dengan memilih nilai Hessian Threshold dan jarak maksimum fitur yang tepat. Kontribusi kedua optimasi waktu deteksi menggunakan metode yang diusulkan. Metode ini hanya menggunakan fitur 3 gambar referensi berdasarkan hasil deteksi sebelumnya. Optimasi waktu deteksi, untuk lintasan dengan 28 gambar referensi, dapat mempersingkat waktu deteksi sebesar 8,72 kali. Pengujian metode yang diusulkan dilakukan menggunakan omnidirectional mobile robot yang berjalan di suatu daerah. Pengujian dilakukan dengan menggunakan metode recall, presisi, akurasi, F-measure, G-measure, dan waktu deteksi. Pengujian deteksi lokasi juga dilakukan berdasarkan metode SIFT untuk dibandingkan dengan metode yang diusulkan. Berdasarkan pengujian, kinerja metode yang diusulkan lebih baik daripada SIFT untuk pengukuran dengan recall 89,67%, akurasi 99,59%, F-measure 93,58%, G-measure 93,87%, dan waktu deteksi 0,365 detik. Metode SIFT hanya lebih baik pada presisi 98,74%. AbstractSelf-location detection or self-localization is one of the capabilities that must be possessed by the mobile robot. The self-localization ability is used to determine the robot position in an area and as a reference to determine the next trip direction. In this research, robot localization was by vision-data based, which was captured by catadioptric-types omnidirectional cameras. The number of closest features between the 360o image captured by the Omni camera and the reference image was the basis for determining location predictions. Image feature extraction uses the Speeded-Up Robust Features (SURF) method. The first contribution of this research is the optimization of detection accuracy by selecting the Hessian Threshold value and the maximum distance of the right features. The second contribution is the optimization of detection time using the proposed method. This method uses only the features of 3 reference images based on the previous detection results. Optimization of detection time, for trajectories with 28 reference images, can shorten the detection time by 8.72 times. Testing the proposed method was done using an omnidirectional mobile robot that walks in an area. Tests carried out using the method of recall, precision, accuracy, F-measure, G-measure, and detection time. Location detection testing was also done based on the SIFT method to be compared with the proposed method. Based on testing, the proposed method performance is better than SIFT for measurements with recall 89.67%, accuracy 99.59%, F-measure 93.58%, G-measure 93.87%, and detection time 0.365 seconds. The SIFT method is only better at precision 98.74%

Pemodelan Konsep dan Rancangan Mekanik sebuah Purwarupa Unmanned Ground Vehicle untuk Pergerakan Omnidirectional

Penggunaan UGV sebagai bagian dari otomasi disektor industri pertanian dilakukan secara intensif sebagai solusi dari masalah tenaga kerja dan produksi. Saat ini UGV yang dikembangkan pada sektor industri pertanian masih terbatas pada kemampuan bermanuvernya. UGV dengan kemampuan bermanuver yang tinggi dibutuhkan untuk melakukan beberapa pekertajaan pertanian dalam rangka untuk meningkatkan fisiensi produksi pertanian. Sehingga pada paper ini diusulkan sebuah ide baru berupa rancangan mekanik UGV untuk memperbaiki kemampuan bermanuver UGV. Paper ini menawarkan sebuah konsep perancangan mekanik untuk mendukung pergerakan omnidirectional sebagai kelebihan pergerakan UGV yang dirancang pada permukaan lahan pertanian. Suatu sistem steering independen dirancang pada UGV ini untuk mendukung mekanisme pergerakan omnidirectional. Sebelum proses pembuatan, konsep, rancangan, dan struktur UGV pertanian yang diusulkan dievaluasi menggunakan simulasi untuk memahami mengenai struktur rangka dan mekanisme geraknya. Pada penelitian ini, analisis struktur dan gerak dilakukan dengan menggunakan perangkat lunak computer aided design. Hasilnya menunjukan bahwa sistem steering yang dirancang dapat digunakan sebagai mekanisme kemudi untuk mendukung pergerakan omnidirectional

Comprehensive Development And Control Of A Path-Trackable Mecanum-Wheeled Robot

This paper presents an intuitively straightforward yet comprehensive approach in developing and controlling a Mecanum-wheeled robot (MWR), with decent path tracking performance by using a simple controller as an end objective. The development starts by implementing two computer ball mice as sensors to realize a simple localization that is immune toward wheel slippage. Then, a linearization method by using open-loop step responses is carried out to linearize the actuations of the robot. Open-loop step response is handy, as it directly portrays the non-linearity of the system, thus achieving effective counteraction. Then, instead of creating a lookup table, polynomial regression is used to generate an equation in which the equation later represents an element of the linearizer. Next, a linear angle-to-gain (LA-G) method is introduced for path tracking control. The method is as easy as just linearly maps the summation of two angles-the angle between immediate and desired positions and the MWR's heading angle, into gains to control the wheels. Unlike the conventional control method which involves inverse kinematics, the LA-G method is directly a displacement-controlled approach and does not require the knowledge of parametric values, such as the robot's dimensions and wheel radius. Finally, all the methods are implemented, and the MWR experimentally demonstrates successfully tracking various paths, by merely using proportional controllers

Localizzazione di un UAV mediante tecnica TOA in sistemi UWB

Questo lavoro di tesi descrive una tecnica di localizzazione 3D di un UAV (Unmanned Aerial Vehicle) in ambiente outdoor mediante analisi numerica. Grazie a quattro nodi ubicati a bordo di un rover o GS (Ground Station), ovvero la testa di un convoglio militare, che interrogano sequenzialmente un nodo posto sull’UAV che si muove di fronte ad essa, è possibile determinare la posizione di quest’ultimo attraverso un algoritmo di multilaterazione. Impiegando la tecnologia UWB (Ultra Wide Band), le distanze tra i due sensori sono misurate con accuratezza centimetrica e la durata della singola misura è dell’ordine del millisecondo. Inoltre, grazie alla tecnica TOA (Time Of Arrival) nella modalità TW-TOF (Two Way-Time Of Flight), la misura della distanza tra due nodi è estratta a partire dal tempo di volo del segnale trasmesso senza la necessità di una sincronizzazione. Per la risoluzione dell’algoritmo di multilaterazione è stato scelto l’algoritmo di Levenberg-Marquardt, valido strumento di risoluzione in forma iterativa dei sistemi non lineari che presenta prestazioni migliori rispetto ad un metodo algebrico di tipo LSM (Least Square Method), che applica il metodo dei minimi quadrati al sistema lineare ottenuto da quello non lineare mediante una modifica delle equazioni. A causa del moto relativo tra l’UAV e la GS, le distanze misurate sono riferite a differenti posizioni dell’UAV nel tempo, e questo fenomeno deve essere considerato nel risolvere l’algoritmo di multilaterazione. In questo contesto, viene proposto di impiegare la stima della velocità relativa dell’UAV lungo la direzione principale di avanzamento che coincide con la coordinata stimata con maggiore precisione. Le distanze misurate sono così opportunamente corrette in base alla velocità stimata, riferite ad una stessa posizione dell’UAV e possono essere impiegate nell’algoritmo di multilaterazione. Analizzando diverse configurazioni dei sensori sulla GS e diversi ordini temporali con cui essi effettuano la misura della distanza, è possibile determinare una configurazione che permette di avere un errore dell’ordine del decimetro per le coordinate trasverse al moto e dell’ordine del centimetro per la coordinata relativa alla direzione principale di avanzamento. Il metodo proposto ha il vantaggio di non dover impiegare alcun dispositivo esterno per la stima della velocità e di non dover sincronizzare i nodi UWB

Indoor Positioning and Navigation

In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot