TH-AB-202-10: Quantifying the Accuracy and Precision of Six Degree-Of-Freedom Motion Estimation for Use in Real-Time Tumor Motion Monitoring During Radiotherapy

2016 ◽  
Vol 43 (6Part44) ◽  
pp. 3858-3859
Author(s):  
J Kim ◽  
D Nguyen ◽  
C Huang ◽  
R O'Brien ◽  
V Caillet ◽  
...  
2005 ◽  
Vol 2 (1) ◽  
pp. 155-165
Author(s):  
Baghdad Science Journal

Many of accurate inertial guided missilc systems need to use more complex mathematical calculations and require a high speed processing to ensure the real-time opreation. This will give rise to the need of developing an effcint


2018 ◽  
Vol 126 (2) ◽  
pp. 236-243 ◽  
Author(s):  
Jung-Ha Kim ◽  
Doan T. Nguyen ◽  
Jeremy T. Booth ◽  
Chen-Yu Huang ◽  
Todsaporn Fuangrod ◽  
...  

2021 ◽  
Author(s):  
Ningning Shi ◽  
Shengtong Wang ◽  
Gaopeng Xue ◽  
Mengfang Liu ◽  
Yaodong Han ◽  
...  

Author(s):  
Alexander Yuen ◽  
Yusuf Altintas

This paper presents a methodology to compensate the tooltip position errors caused by the geometric errors of a three-axis gantry type micromill integrated with a six degree-of-freedom (6DOF) rotary magnetic table. A geometric error-free ideal forward kinematic model of the nine-axis machine has been developed using homogenous transformation matrices (HTMs). The geometric errors of each linear axis, which include one positioning, two straightness, pitch, roll, and yaw errors, are measured with a laser interferometer and fit to quintic polynomial functions in the working volume of the machine. The forward kinematic model is modified to include the geometric errors which, when subtracted from the ideal kinematic model, gives the deviation between the desired tooltip position with and without geometric errors. The position commands of the six degree-of-freedom rotary magnetic table are modified in real time to compensate for the tooltip deviation using a gradient descent algorithm. The algorithm is simulated and verified experimentally on the nine-axis micromill controlled by an in-house developed virtual/real-time open computer numerical controlled (CNC) system.


Author(s):  
Grant Rudd ◽  
Liam Daly ◽  
Filip Cuckov

Purpose This paper aims to present an intuitive control system for robotic manipulators that pairs a Leap Motion, a low-cost optical tracking and gesture recognition device, with the ability to record and replay trajectories and operation to create an intuitive method of controlling and programming a robotic manipulator. This system was designed to be extensible and includes modules and methods for obstacle detection and dynamic trajectory modification for obstacle avoidance. Design/methodology/approach The presented control architecture, while portable to any robotic platform, was designed to actuate a six degree-of-freedom robotic manipulator of our own design. From the data collected by the Leap Motion, the manipulator was controlled by mapping the position and orientation of the human hand to values in the joint space of the robot. Additional recording and playback functionality was implemented to allow for the robot to repeat the desired tasks once the task had been demonstrated and recorded. Findings Experiments were conducted on our custom-built robotic manipulator by first using a simulation model to characterize and quantify the robot’s tracking of the Leap Motion generated trajectory. Tests were conducted in the Gazebo simulation software in conjunction with Robot Operating System, where results were collected by recording both the real-time input from the Leap Motion sensor, and the corresponding pose data. The results of these experiments show that the goal of accurate and real-time control of the robot was achieved and validated our methods of transcribing, recording and repeating six degree-of-freedom trajectories from the Leap Motion camera. Originality/value As robots evolve in complexity, the methods of programming them need to evolve to become more intuitive. Humans instinctively teach by demonstrating the task to a given subject, who then observes the various poses and tries to replicate the motions. This work aims to integrate the natural human teaching methods into robotics programming through an intuitive, demonstration-based programming method.


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