The TurboRocket Trajectory Determination System

2020 ◽  
Author(s):  
Rene N. Rezende ◽  
Lucas R. Alves
Keyword(s):  
Determination System ◽  
Trajectory Determination

Alternate Trajectory Determination Using Multimode Automated Robotic Vehicle with Line Following and Object Following Mode

2018 ◽  
Vol 8 (3) ◽  
pp. 46
Author(s):  
Varun Kumar ◽  
Lakshya Gaur ◽  
Arvind Rehalia
Keyword(s):  
Ultrasonic Sensor ◽  
Robotic Assembly ◽  
Voltage Regulator ◽  
Automated Vehicle ◽  
Dc Motors ◽  
Arduino Uno ◽  
Robotic Vehicle ◽  
Line Following ◽  
Selection Of ◽  
Trajectory Determination

In this paper the authors have explained the development of robotic vehicle prepared by them, which operates autonomously and is not controlled by the users, except for selection of modes. The different modes of the automated vehicle are line following, object following and object avoidance with alternate trajectory determination. The complete robotic assembly is mounted on a chassis comprising of Arduino Uno, Servo motors, HC-SRO4 (Ultrasonic sensor), DC motors (Geared), L293D Motor Driver, IR proximity sensors, Voltage Regulator along with castor wheel and two normal wheels.

scholarly journals Error estimation on extracorporeal trajectory determination from body scans

2021 ◽  
Author(s):  
F. Riva ◽  
U. Buck ◽  
K. Buße ◽  
R. Hermsen ◽  
E. J. A. T. Mattijssen ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Soft Tissue ◽  
Supine Position ◽  
Post Mortem ◽  
Surface Scanning ◽  
3D Data ◽  
Gravitational Pull ◽  
Scanned Images ◽  
Source Of Error ◽  
Trajectory Determination

AbstractThis study explores the magnitude of two sources of error that are introduced when extracorporeal bullet trajectories are based on post-mortem computed tomography (PMCT) and/or surface scanning of a body. The first source of error is caused by an altered gravitational pull on soft tissue, which is introduced when a body is scanned in another position than it had when hit. The second source of error is introduced when scanned images are translated into a virtual representation of the victim’s body. To study the combined magnitude of these errors, virtual shooting trajectories with known vertical angles through five “victims” (live test persons) were simulated. The positions of the simulated wounds on the bodies were marked, with the victims in upright positions. Next, the victims were scanned in supine position, using 3D surface scanning, similar to a body’s position when scanned during a PMCT. Seven experts, used to working with 3D data, were asked to determine the bullet trajectories based on the virtual representations of the bodies. The errors between the known and determined trajectories were analysed and discussed. The results of this study give a feel for the magnitude of the introduced errors and can be used to reconstruct actual shooting incidents using PMCT data.

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