TH-AB-303-03: Real-Time Error Estimation for Real-Time Motion Prediction

2015 ◽  
Vol 42 (6) ◽  
pp. 3711-3711
Author(s):  
D Moore ◽  
A Sawant
Keyword(s):  
Real Time ◽  
Error Estimation ◽  
Motion Prediction ◽  
Time Error ◽  
Time Motion

Real-time motion prediction using the chromatic offset of line scan cameras

2017 ◽  
Vol 65 (6) ◽  
Author(s):  
Florian Pfaff ◽  
Georg Maier ◽  
Mikhail Aristov ◽  
Benjamin Noack ◽  
Robin Gruna ◽  
...  
Keyword(s):  
Real Time ◽  
State Of The Art ◽  
Bulk Material ◽  
Separation Process ◽  
Motion Prediction ◽  
Line Scan ◽  
Time Motion ◽  
Sorting Process

AbstractState-of-the-art optical belt sorters commonly employ line scan cameras and use simple assumptions to predict each particle's movement, which is required for the separation process. Previously, we have equipped an experimental optical belt sorter with an area scan camera and were able to show that tracking the particles of the bulk material results in an improvement of the predictions and thus also the sorting process. In this paper, we use the slight gap between the sensor lines of an RGB line scan camera to derive information about the particles' movements in real-time. This approach allows improving the predictions in optical belt sorters without necessitating any hardware modifications.

scholarly journals Fast Online Coordinate Correction of a Multi-Sensor for Object Identification in Autonomous Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2006
Author(s):  
Wooyoung Lee ◽  
Minchul Lee ◽  
Myoungho Sunwoo ◽  
Kichun Jo
Keyword(s):  
Real Time ◽  
Error Estimation ◽  
Correction Method ◽  
Object Identification ◽  
Computational Effort ◽  
Error Modeling ◽  
Estimation Methods ◽  
Time Error ◽  
Sensor Error ◽  
Coordinate Correction

Multi-sensor perception systems may have mismatched coordinates between each sensor even if the sensor coordinates are converted to a common coordinate. This discrepancy can be due to the sensor noise, deformation of the sensor mount, and other factors. These mismatched coordinates can seriously affect the estimation of a distant object’s position and this error can result in problems with object identification. To overcome these problems, numerous coordinate correction methods have been studied to minimize coordinate mismatching, such as off-line sensor error modeling and real-time error estimation methods. The first approach, off-line sensor error modeling, cannot cope with the occurrence of a mismatched coordinate in real-time. The second approach, using real-time error estimation methods, has high computational complexity due to the singular value decomposition. Therefore, we present a fast online coordinate correction method based on a reduced sensor position error model with dominant parameters and estimate the parameters by using rapid math operations. By applying the fast coordinate correction method, we can reduce the computational effort within the necessary tolerance of the estimation error. By experiments, the computational effort was improved by up to 99.7% compared to the previous study, and regarding the object’s radar the identification problems were improved by 94.8%. We conclude that the proposed method provides sufficient correcting performance for autonomous driving applications when the multi-sensor coordinates are mismatched.

Real-time error detection techniques based on FPGA

2013 ◽  
Vol 33 (5) ◽  
pp. 1459-1462
Author(s):  
Xiaoming JU ◽  
Jiehao ZHANG ◽  
Yizhong ZHANG
Keyword(s):  
Real Time ◽  
Error Detection ◽  
Time Error ◽  
Detection Techniques

A real-time motion planning scheme for collaborative robots using HRI-based cost function

2021 ◽  
Vol 8 (1) ◽  
pp. 42
Author(s):  
Khawaja Fahad Iqbal ◽  
Akira Kanazawa ◽  
Silvia Romana Ottaviani ◽  
Jun Kinugawa ◽  
Kazuhiro Kosuge
Keyword(s):  
Motion Planning ◽  
Cost Function ◽  
Real Time ◽  
Collaborative Robots ◽  
Time Motion ◽  
Planning Scheme

Real-time motion tracking in image-guided oral implantology

2008 ◽  
Vol 4 (4) ◽  
pp. 339-347 ◽  
Author(s):  
Xiaojun Chen ◽  
Yanping Lin ◽  
Yiqun Wu ◽  
Chengtao Wang
Keyword(s):  
Real Time ◽  
Motion Tracking ◽  
Image Guided ◽  
Time Motion ◽  
Oral Implantology
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