A Low-cost, Wearable Opto-inertial 6 DOF Hand Pose Tracking System for VR

In this paper, a low cost, wearable six Degree of Freedom (6-DOF) hand pose tracking system is proposed for Virtual Reality applications. It is designed for use with an integrated hand exoskeleton system for kinesthetic haptic feedback. The tracking system consists of an Infrared (IR) based optical tracker with low cost mono-camera and inertial and magnetic measurement unit. Image processing is done on LabVIEW software to extract the 3-DOF position from two IR targets and Magdwick filter has been implemented on Mbed LPC1768 board to obtain orientation data. Six DOF hand tracking outputs filtered and synchronized on LabVIEW software are then sent to the Unity Virtual environment via User Datagram Protocol (UDP) stream. Experimental results show that this low cost and compact system has a comparable performance of minimal Jitter with position and orientation Root Mean Square Error (RMSE) of less than 0.2 mm and 0.15 degrees, respectively. Total Latency of the system is also less than 40 ms

Development of a Low-Cost 6 DOF Brick Tracking System for Use in Advanced Gas-Cooled Reactor Model Tests

This paper presents the design of a low-cost, compact instrumentation system to enable six degree of freedom motion tracking of acetal bricks within an experimental model of a cracked Advanced Gas-Cooled Reactor (AGR) core. The system comprises optical and inertial sensors and capitalises on the advantages offered by data fusion techniques. The optical system tracks LED indicators, allowing a brick to be accurately located even in cluttered images. The LED positions are identified using a geometrical correspondence algorithm, which was optimised to be computationally efficient for shallow movements, and complex camera distortions are corrected using a versatile Incident Ray-Tracking calibration. Then, a Perspective-Ray-based Scaled Orthographic projection with Iteration (PRSOI) algorithm is applied to each LED position to determine the six degree of freedom pose. Results from experiments show that the system achieves a low Root Mean Squared (RMS) error of 0.2296 mm in x, 0.3943 mm in y, and 0.0703 mm in z. Although providing an accurate measurement solution, the optical tracking system has a low sample rate and requires the line of sight to be maintained throughout each test. To increase the robustness, accuracy, and sampling frequency of the system, the optical system can be augmented with an Inertial Measurement Unit (IMU). This paper presents a method to integrate the optical system and IMU data by accurately timestamping data from each set of sensors and aligning the two coordinate axes. Once miniaturised, the developed system will be used to track smaller components within the AGR models that cannot be tracked with current instrumentation, expanding reactor core modelling capabilities

Review and classification of vision-based localisation techniques in unknown environments

International audienceThis study presents a review of the state-of-the-art and a novel classification of current vision-based localisation techniques in unknown environments. Indeed, because of progresses made in computer vision, it is now possible to consider vision-based systems as promising navigation means that can complement traditional navigation sensors like global navigation satellite systems (GNSSs) and inertial navigation systems. This study aims to review techniques employing a camera as a localisation sensor, provide a classification of techniques and introduce schemes that exploit the use of video information within a multi-sensor system. In fact, a general model is needed to better compare existing techniques in order to decide which approach is appropriate and which are the innovation axes. In addition, existing classifications only consider techniques based on vision as a standalone tool and do not consider video as a sensor among others. The focus is addressed to scenarios where no a priori knowledge of the environment is provided. In fact, these scenarios are the most challenging since the system has to cope with objects as they appear in the scene without any prior information about their expected position

An innovative navigation and guidance system for small unmanned aircraft using low-cost sensors

Purpose - The purpose of this paper is to design a compact, light and relatively inexpensive navigation and guidance system capable of providing the required navigation performance (RNP) in all phases of flight of small unmanned aircrafts (UA), with a special focus on precision approach and landing. Design/methodology/approach - Two multi-sensor architectures for navigation and guidance of small UA are proposed and compared in this paper. These architectures are based, respectively, on a standard extended Kalman filter (EKF) approach and a more advanced unscented Kalman filter (UKF) approach for data fusion of global navigation satellite systems (GNSS), micro-electro-mechanical system (MEMS)-based inertial measurement unit (IMU) and vision-based navigation (VBN) sensors. Findings - The EKF-based VBN-IMU-GNSS-aircraft dynamics model (ADM) (VIGA) system and the UKF-based system (VIGA+) performances are compared in a small UA integration scheme (i.e. AEROSONDE UA platform) exploring a representative cross-section of this UA operational flight envelope, including high-dynamics manoeuvres and CAT-I to CAT-III precision approach tasks. The comparison shows that the position and attitude accuracy of the proposed VIGA and VIGA+ systems are compatible with the RNP specified in the various UA flight profiles, including precision approach down to CAT-II. Originality/value - The novelty aspect is the augmentation by ADM in both architectures to compensate for the MEMS-IMU sensor shortcomings in high-dynamics attitude determination tasks. Additionally, the ADM measurements are pre-filtered by an UKF with the purpose of increasing the ADM attitude solution stability time in the UKF-based system

A Tangible Solution for Hand Motion Tracking in Clinical Applications

Objective real-time assessment of hand motion is crucial in many clinical applications including technically-assisted physical rehabilitation of the upper extremity. We propose an inertial-sensor-based hand motion tracking system and a set of dual-quaternion-based methods for estimation of finger segment orientations and fingertip positions. The proposed system addresses the specific requirements of clinical applications in two ways: (1) In contrast to glove-based approaches, the proposed solution maintains the sense of touch. (2) In contrast to previous work, the proposed methods avoid the use of complex calibration procedures, which means that they are suitable for patients with severe motor impairment of the hand. To overcome the limited significance of validation in lab environments with homogeneous magnetic fields, we validate the proposed system using functional hand motions in the presence of severe magnetic disturbances as they appear in realistic clinical settings. We show that standard sensor fusion methods that rely on magnetometer readings may perform well in perfect laboratory environments but can lead to more than 15 cm root-mean-square error for the fingertip distances in realistic environments, while our advanced method yields root-mean-square errors below 2 cm for all performed motions.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli