Lessons Learned from OSIRIS-Rex Autonomous Navigation Using Natural Feature Tracking

The Origins, Spectral Interpretation, Resource Identification, Security-Regolith Explorer (Osiris-REx) spacecraft is scheduled to launch in September, 2016 to embark on an asteroid sample return mission. It is expected to rendezvous with the asteroid, Bennu, navigate to the surface, collect a sample (July 20), and return the sample to Earth (September 23). The original mission design called for using one of two Flash Lidar units to provide autonomous navigation to the surface. Following Preliminary design and initial development of the Lidars, reliability issues with the hardware and test program prompted the project to begin development of an alternative navigation technique to be used as a backup to the Lidar. At the critical design review, Natural Feature Tracking (NFT) was added to the mission. NFT is an onboard optical navigation system that compares observed images to a set of asteroid terrain models which are rendered in real-time from a catalog stored in memory on the flight computer. Onboard knowledge of the spacecraft state is then updated by a Kalman filter using the measured residuals between the rendered reference images and the actual observed images. The asteroid terrain models used by NFT are built from a shape model generated from observations collected during earlier phases of the mission and include both terrain shape and albedo information about the asteroid surface. As a result, the success of NFT is highly dependent on selecting a set of topographic features that can be both identified during descent as well as reliably rendered using the shape model data available. During development, the OSIRIS-REx team faced significant challenges in developing a process conducive to robust operation. This was especially true for terrain models to be used as the spacecraft gets close to the asteroid and higher fidelity models are required for reliable image correlation. This paper will present some of the challenges and lessons learned from the development of the NFT system which includes not just the flight hardware and software but the development of the terrain models used to generate the onboard rendered images

Automatic camera pose initialization, using scale, rotation and luminance invariant natural feature tracking

The solution to the camera registration and tracking problem serves Augmented Reality, in order to provide an enhancement to the user’s cognitive perception of the real world and his/her situational awareness. By analyzing the five most representative tracking and feature detection techniques, we have concluded that the Camera Pose Initialization (CPI) problem, a relevant sub-problem in the overall camera tracking problem, is still far from being solved using straightforward and non-intrusive methods. The assessed techniques often use user inputs (i.e. mouse clicking) or auxiliary artifacts (i.e. fiducial markers) to solve the CPI problem. This paper presents a novel approach to real-time scale, rotation and luminance invariant natural feature tracking, in order to solve the CPI problem using totally automatic procedures. The technique is applicable for the case of planar objects with arbitrary topologies and natural textures, and can be used in Augmented Reality. We also present a heuristic method for feature clustering, which has revealed to be efficient and reliable. The presented work uses this novel feature detection technique as a baseline for a real-time and robust planar texture tracking algorithm, which combines optical flow, backprojection and template matching techniques. The paper presents also performance and precision results of the proposed technique

Automatic camera pose initialization, using scale, rotation and luminance invariant natural feature tracking

The solution to the camera registration and tracking problem serves Augmented Reality, in order to provide an enhancement to the user’s cognitive perception of the real world and his/her situational awareness. By analyzing the five most representative tracking and feature detection techniques, we have concluded that the Camera Pose Initialization (CPI) problem, a relevant sub-problem in the overall camera tracking problem, is still far from being solved using straightforward and non-intrusive methods. The assessed techniques often use user inputs (i.e. mouse clicking) or auxiliary artifacts (i.e. fiducial markers) to solve the CPI problem. This paper presents a novel approach to real-time scale, rotation and luminance invariant natural feature tracking, in order to solve the CPI problem using totally automatic procedures. The technique is applicable for the case of planar objects with arbitrary topologies and natural textures, and can be used in Augmented Reality. We also present a heuristic method for feature clustering, which has revealed to be efficient and reliable. The presented work uses this novel feature detection technique as a baseline for a real-time and robust planar texture tracking algorithm, which combines optical flow, backprojection and template matching techniques. The paper presents also performance and precision results of the proposed technique.info:eu-repo/semantics/publishedVersio

AUGMENTED REALITY SEBAGAI MEDIA PEMBELAJARAN PERANGKAT KERAS KOMPUTER DENGAN FAST CORNER DAN NATURAL FEATURE TRACKING

Teknologi yang semakin berkembang membuat teknologi dapat digunakan sebagai media edukasi, salah satu media edukasi yang mulai banyak digunakan adalah Augmented Reality, yaitu teknologi yang mengintegrasikan objek yang dibuat oleh komputer, dua dimensi atau tiga dimensi, ke lingkungan nyata di sekitar pengguna secara langsung. Augmented Reality ini dapat dimanfaatkan sebagai media pengenalan perangkat keras komputer dalam bentuk 3D dengan menggunakan algoritma FAST corner detection dan metode natural feature tracking. Dengan adanya Augmented Reality ini, siswa dapat mengenal perangkat keras komputer (unit proses dan unit penyimpanan) dan dapat meningkatkan minat belajar siswa dalam perangkat keras komputer. Dari hasil pengujian sudut yang telah dilakukan pada dua smartphone, pada sudut 21º - 90º, marker dapat dibaca oleh smartphone, sedangkan untuk sudut 20º, marker tidak terbaca sehingga objek tidak akan muncul pada layar smartphone. Dan pengujian berdasarkan waktu respon terhadap munculnya objek tiga dimensi pada kedua smartphone memiliki waktu rata rata kurang dari 2 detik

Revisiting OSIRIS-REx Touch-And-Go (TAG) Performance Given the Realities of Asteroid Bennu

The Origins, Spectral Interpretation, Resource Identification, and SecurityRegolith Explorer (OSIRIS-REx) mission is a NASA New Frontiers mission that launched in 2016 and rendezvoused with the near-Earth asteroid (101955) Bennu in late 2018. Upon arrival, the surface of Bennu was found to be much rockier than expected. The original Touch-and-Go (TAG) requirement for sample collection was to deliver the spacecraft to a site with a 25-meter radius; however, the largest hazard-free sites are no larger than 8 meters in radius. To accommodate the dearth of safe sample collection sites, the project reevaluated all aspects of flight system performance pertaining to TAG in order to account for the demonstrated performance of the spacecraft and navigation prediction accuracies. More-over, the project has base lined on board natural feature tracking instead of lidar for providing the on board navigation state update during the TAG sequence. This paper summarizes the improvements in error source estimation, enhancements in on board trajectory correction, and results of recent Monte Carlo simulation to en-able sample collection with the given constraints. TAG delivery and on board navigation performance are presented for the final four candidate TAG sites

Natural Feature Tracking Augmented Reality for On-Site Assembly Assistance Systems

We introduce a natural feature tracking approach that facilitates the tracking of rigid objects for an on-site assembly assistance system. The tracking system must track multiple circuit boards without added fiducial markers, and they are manipulated by the user. We use a common SIFT feature matching detector enhanced with a probability search. This search estimates how likely a set of query descriptors belongs to a particular object. The method was realized and tested. The results show that the probability search enhanced the identification of different circuit boards

Augmented reality panduan belajar wudhu menggunakan algoritma Natural Feature Tracking (NFT) berbasis android

INDONESIA Wudhu merupakan suatu hal yang paling penting dalam agama Islam yang merupakan salah satu syarat syah shalat yang dilakukan sebelum shalat, oleh karena itu diperlukan aplikasi yang dapat membantu untuk proses pembelajaran wudhu. Augmented Reality (AR) adalah suatu lingkungan yang memasukkan objek virtual 3D kedalam lingkungan nyata secara rel-time, aplikasi ini merupakan aplikasi yang dapat berjalan pada platform android dan menggunakan marker untuk melakukan deteksi objek. Metode pengembangan yang digunakan yaitu metode Rational Unified Process (RUP) yang memiliki ciri utama dari metode ini adalah menggunakan use-case driven dan pendekatan interative untuk siklus pengembangan perangkat lunak. Desain perancangan menggunakan UML, tools yang digunakan dalam pembuatan aplikasi ini yaitu unity dan library vuforia. Algoritma yang digunakan yaitu Natural Feature Tracking (NFT) serta Fast Corner Detection untuk proses menentukan titik-titik dalam proses pendeteksian marker. Pengujian aplikasi ini menggunakan metode Black-box yang menguji fungsionalitas dari aplikasi tersebut, dan pengujian beta dengan membuat kuesioner yang ditujukan untuk menghasilkan validasi ahli, hasil uji dari aplikasi ini menunjukan dapat digunakan untuk proses belajar mengenai tata cara wudhu. ENGLISH Ablution is a the most important part of islamic is one of the requirements shah prayer that were conducted before prayer, hence required application that may help to learning ablution. Augmented reality (AR) is a environment causes object virtual 3d into the real environment in rel-time, the application is application that can run on a platform android and use marker to do detection object. Method of development used that is a method of rational the unified process (RUP) having the main characteristics of of this method is use use-case driven and approach interative to the cycle of development software. Design using uml design, tools used in making application is unity and libraries vuforia. The algorithms that used that is natural features tracking ( nft and fast corner detection to process of ascertaining points in the process detection marker. Testing this application uses the method black-box who tested functionality of such application, and beta testing by making a questionnaire aimed at producing validation expert, testing shows of application this really shows you can be used to the learning process regarding the procedures of ablution

Model Addie Pada Augmented Reality Hewan Purba Bersayap Menggunakan Algoritma Fast Corner Detection Dan NFT

Pengenalan objek menggunakan Augmented Reality sudah menjadi trend di dunia media promosi kepada anak-anak usia dini hingga masyarakat umum. Objek yang digunakan berupa hewan, tumbuhan, huruf, angka dan lain lain. Penelitian ini menggunakan objek berupa hewan purbakala yang sudah punah sejak jutaan tahun yang lalu. Tujuan penelitian ini yaitu berfokus pada pengenalan hewan-hewan purbakala utnuk anak-anak bahwa terdapat hewan reptil yang berpostur raksasa telah hidup di zaman dahulu. Meskipun reptil ini telah punah, mereka akan menggunakan Augmented Reality pada penelitian ini sebagai media informasi yang menarik. Model ADDIE dikembangkan pada penelitian ini yang disusun oleh Natural Feature Tracking (NFT) menggunakan Algoritma FAST Corner Detection ke arah tingkat keberhasilan yang tinggi. Hasil pengujian pada beberapa versi android berupa objek gambar memiliki tingkat keakuratan yang tinggi melalui perhitungan FAST Corner Detection dan pengujian metode NFT. Semakin tinggi rating objek yang ditunjukkan pada vuforia, maka semakin tinggi ketelitian dalam mendeteksi objek pada marker