Force control of ER fluid based haptic device in virtual environment

2007 ◽  
Author(s):  
Young-Min Han ◽  
Pil-Soon Kang ◽  
Min-Sang Seong ◽  
Seung-Bok Choi
2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Faraz Shah ◽  
Ilia G. Polushin

The paper deals with the design of control algorithms for virtual reality based telerobotic system with haptic feedback that allows for the remote control of the vertical drilling operation. The human operator controls the vertical penetration velocity using a haptic device while simultaneously receiving the haptic feedback from the locally implemented virtual environment. The virtual environment is rendered as a virtual spring with stiffness updated based on the estimate of the stiffness of the rock currently being cut. Based on the existing mathematical models of drill string/drive systems and rock cutting/penetration process, a robust servo controller is designed which guarantees the tracking of the reference vertical penetration velocity of the drill bit. A scheme for on-line estimation of the rock intrinsic specific energy is implemented. Simulations of the proposed control and parameter estimation algorithms have been conducted; consequently, the overall telerobotic drilling system with a human operator controlling the process using PHANTOM Omni haptic device is tested experimentally, where the drilling process is simulated in real time in virtual environment.


1993 ◽  
Vol 26 (2) ◽  
pp. 535-540
Author(s):  
S. Kawaji ◽  
T. Maeda ◽  
N. Matsunaga

Author(s):  
Xiaowei Dai ◽  
Yuru Zhang ◽  
Dangxiao Wang

Maximum virtual stiffness is a critical performance measure for haptic devices. Stable haptic interaction is necessary for realistic feeling of virtual environment. The virtual environment is determined by the application and device. To ensure the stable haptic interaction, the virtual environment must be suitable for the device. Therefore, the virtual stiffness should not be greater than the minimum value of maximum virtual stiffness that a haptic device can stably render in the workspace. This paper proposes a method, utilizing the eigenvalue and eigenvector of stiffness matrix in joint space, to analyze and measure the maximum virtual stiffness distribution in the work space of a haptic device. Therefore, for a given haptic device, the maximum virtual stiffness at each position and orientation can be forecasted by this method. A new sufficient condition for haptic stability is also presented in the view of driven motor in this paper. A series experiments validate the effectiveness of this method.


Author(s):  
Norali Pernalete ◽  
Amar Raheja ◽  
Stephanie Carey

In this paper, we discuss the possibility to determine assessment metrics for eye-hand coordination and upper-limb disability therapy, using a mapping between a robotic haptic device to a virtual environment and a training algorithm based on Complex Valued Neural Networks that will calculate how close a set movement pattern is in relationship with that traced by a healthy individual. Most of the current robotic systems’ therapy relies on the patient’s performance on standardized clinical tests such as the functional independence measure (FIM), and the upper limb subsection of the Fugl-Meyer (FM) scales. These systems don’t have other standardized metrics for assessment purposes. There is a need to establish a more intelligent and tailored therapy that could be implemented for patients to use at home in between therapy sessions, or in the long term. This therapy should be based on performance data gathered by the robotic/computer system that will provide an assessment procedure with improved objectivity and precision. A set of complex and movement demanding virtual environments, representing various levels of difficulty labyrinths was developed in a virtual environment. The participants were instructed to use a haptic device (Omni) to follow the trajectories. This was completed while video data were collected using a Vicon motion capture system. Readings of traced trajectories, time, and upper limb motions are recorded for further analysis.


2021 ◽  
Author(s):  
Linda Feenstra ◽  
Umberto Scarcia ◽  
Riccardo Zanella ◽  
Roberto Meattini ◽  
Davide Chiaravalli ◽  
...  

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