Tracking of User Position and Orientation by Stereo Measurement of Infrared Markers and Orientation Sensing

2004 ◽  
Author(s):  
M. Maeda ◽  
T. Ogawa ◽  
K. Kiyokawa ◽  
H. Takemura
Keyword(s):  
Position And Orientation

scholarly journals CNN Training Using 3D Virtual Models for Assisted Assembly with Mixed Reality and Collaborative Robots

2021 ◽  
Vol 11 (9) ◽  
pp. 4269
Author(s):  
Kamil Židek ◽  
Ján Piteľ ◽  
Michal Balog ◽  
Alexander Hošovský ◽  
Vratislav Hladký ◽  
...  
Keyword(s):  
Mixed Reality ◽  
Current Trend ◽  
Robot Vision ◽  
Processing Unit ◽  
Single Shot ◽  
Vision Systems ◽  
Collaborative Robots ◽  
Training Time ◽  
Position And Orientation ◽  
Collaborative Robot

The assisted assembly of customized products supported by collaborative robots combined with mixed reality devices is the current trend in the Industry 4.0 concept. This article introduces an experimental work cell with the implementation of the assisted assembly process for customized cam switches as a case study. The research is aimed to design a methodology for this complex task with full digitalization and transformation data to digital twin models from all vision systems. Recognition of position and orientation of assembled parts during manual assembly are marked and checked by convolutional neural network (CNN) model. Training of CNN was based on a new approach using virtual training samples with single shot detection and instance segmentation. The trained CNN model was transferred to an embedded artificial processing unit with a high-resolution camera sensor. The embedded device redistributes data with parts detected position and orientation into mixed reality devices and collaborative robot. This approach to assisted assembly using mixed reality, collaborative robot, vision systems, and CNN models can significantly decrease assembly and training time in real production.

scholarly journals Kinematic of the Position and Orientation Synchronization of the Posture of a n DoF Upper-Limb Exoskeleton with a Virtual Object in an Immersive Virtual Reality Environment

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1069
Author(s):  
Deyby Huamanchahua ◽  
Adriana Vargas-Martinez ◽  
Ricardo Ramirez-Mendoza
Keyword(s):  
Virtual Reality ◽  
Upper Limb ◽  
Human Performance ◽  
Early Stage ◽  
Inverse Kinematic ◽  
Virtual Object ◽  
Immersive Virtual Reality ◽  
Virtual Reality Environment ◽  
Upper Limb Exoskeleton ◽  
Position And Orientation

Exoskeletons are an external structural mechanism with joints and links that work in tandem with the user, which increases, reinforces, or restores human performance. Virtual Reality can be used to produce environments, in which the intensity of practice and feedback on performance can be manipulated to provide tailored motor training. Will it be possible to combine both technologies and have them synchronized to reach better performance? This paper consists of the kinematics analysis for the position and orientation synchronization between an n DoF upper-limb exoskeleton pose and a projected object in an immersive virtual reality environment using a VR headset. To achieve this goal, the exoskeletal mechanism is analyzed using Euler angles and the Pieper technique to obtain the equations that lead to its orientation, forward, and inverse kinematic models. This paper extends the author’s previous work by using an early stage upper-limb exoskeleton prototype for the synchronization process.

scholarly journals Modular Approach for Odometry Localization Method for Vehicles with Increased Maneuverability

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 79
Author(s):  
Chenlei Han ◽  
Michael Frey ◽  
Frank Gauterin
Keyword(s):  
Steering System ◽  
Vehicle Control ◽  
Modular Approach ◽  
Route Guidance ◽  
State Variables ◽  
Simulation Environment ◽  
Localization Method ◽  
State Estimators ◽  
Position And Orientation ◽  
Guidance Information

Localization and navigation not only serve to provide positioning and route guidance information for users, but also are important inputs for vehicle control. This paper investigates the possibility of using odometry to estimate the position and orientation of a vehicle with a wheel individual steering system in omnidirectional parking maneuvers. Vehicle models and sensors have been identified for this application. Several odometry versions are designed using a modular approach, which was developed in this paper to help users to design state estimators. Different odometry versions have been implemented and validated both in the simulation environment and in real driving tests. The evaluated results show that the versions using more models and using state variables in models provide both more accurate and more robust estimation.

scholarly journals Camera and inertial sensor fusion for the PnP problem: algorithms and experimental results

2021 ◽  
Vol 32 (4) ◽  
Author(s):  
Luigi D’Alfonso ◽  
Emanuele Garone ◽  
Pietro Muraca ◽  
Paolo Pugliese
Keyword(s):  
Pose Estimation ◽  
Good Accuracy ◽  
Inertial Sensor ◽  
Experimental Tests ◽  
Inertial Measurement Units ◽  
Magnetic Vector ◽  
Inertial Measurement ◽  
The Earth ◽  
Measurement Units ◽  
Position And Orientation

AbstractIn this work, we face the problem of estimating the relative position and orientation of a camera and an object, when they are both equipped with inertial measurement units (IMUs), and the object exhibits a set of n landmark points with known coordinates (the so-called Pose estimation or PnP Problem). We present two algorithms that, fusing the information provided by the camera and the IMUs, solve the PnP problem with good accuracy. These algorithms only use the measurements given by IMUs’ inclinometers, as the magnetometers usually give inaccurate estimates of the Earth magnetic vector. The effectiveness of the proposed methods is assessed by numerical simulations and experimental tests. The results of the tests are compared with the most recent methods proposed in the literature.

Comparative repeatability of guide-pin axis positioning in computer-assisted and manual femoral head resurfacing arthroplasty

2007 ◽  
Vol 221 (7) ◽  
pp. 713-724 ◽  
Author(s):  
A Hodgson ◽  
N Helmy ◽  
B A Masri ◽  
N V Greidanus ◽  
K B Inkpen ◽  
...  
Keyword(s):  
Femoral Head ◽  
Computer Assisted Surgery ◽  
Hip Resurfacing ◽  
Computer Assisted ◽  
Comparable Amount ◽  
Hip Resurfacing Arthroplasty ◽  
Resurfacing Arthroplasty ◽  
Surgeon Experience ◽  
Position And Orientation ◽  
Version Measurement

The orientation of the femoral component in hip resurfacing arthroplasty affects the likelihood of loosening and fracture. Computer-assisted surgery has been shown to improve significantly the surgeon's ability to achieve a desired position and orientation; nevertheless, both bias and variability in positioning remain and can potentially be improved. The authors recently developed a computer-assisted surgical (CAS) technique to guide the placement of the pin used in femoral head resurfacing arthroplasty and showed that it produced significantly less variation than a typical manual technique in varus/valgus placement relative to a pre-operatively determined surgical plan while taking a comparable amount of time. In the present study, the repeatability of both the CAS and manual techniques is evaluated in order to estimate the relative contributions to overall variability of surgical technique (CAS versus manual), surgeon experience (novice versus experienced), and other sources of variability (e.g. across specimens and across surgeons). This will enable further improvements in the accuracy of CAS techniques. Three residents/fellows new to femoral head resurfacing and three experienced hip arthroplasty surgeons performed 20-30 repetitions of each of the CAS and manual techniques on at least one of four cadaveric femur specimens. The CAS system had markedly better repeatability (1.2°) in varus/valgus placement relative to the manual technique (2.8°), slightly worse repeatability in version (4.4° versus 3.2°), markedly better repeatability in mid-neck placement (0.7 mm versus 2.5 mm), no significant dependence on surgeon skill level (in contrast to the manual technique), and took significantly less time (50 s versus 123 s). Proposed improvements to the version measurement process showed potential for reducing the standard deviation by almost two thirds. This study supports the use of CAS for femoral head resurfacing as it is quicker than the manual technique, independent of surgeon experience, and demonstrates improved repeatability.

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