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Research at the haptics lab focusses on many different topics, the field of haptics being inherently inter-disciplinary. Some of the areas we concentrate on are
- Medical and surgical applications of Haptics
- Studying the cognition of touch, and kinesthesis
- Teleoperation and human-machine systems
We also have been working on an open source haptics API called H3D, developed by the people at SenseGraphics. It is an a cross-platform, scene-graph API, written in C++ and uses openGL for the graphics rendering. X3D is the format used for displaying the 3D images. Information about our work at the lab is given below. If you would like to know more, feel free to contact us at tburg@clemson.edu
H3D and the Quanser 5 DOF haptic interface
We have worked on H3D and developed a driver to work with the Quanser 5 Degree of Freeedom Haptic Wand. Prior to this, the device wasn't fully functional with H3D. If you would like a copy of the driver, kindly contact us and we will be happy to provide it.
Medical and Surgical Applications of Haptics
The use of haptics for medical purposes, and for surgery is being investigated. Training for surgeons is one area we are particularly interested in. Conventional methods of training surgeons such as those that use just virtual reality fail to produce a realistic environment, and also lack the vital element of tactile feedback. We are working on incorporating this additional dimension to surgical training in order to prepare surgeons for real surgery, where experience and familiarity with procedure is crucial.
Along with IBIOE, we are working with Medical University of South Carolina(MUSC) to add haptic interation to computer aided maxillofacial prosthetics, for a more easier and natural way of creating prosthetic parts for surgical reconstruction purposes. For more details about the collaborative project with MUSC, click here.
The cognition of touch, and kinesthesis
The cognizance behind the perception of touch and tactile feedback in general is largely an under-investigated area. Haptic technology makes it possible to quantitatively set and measure values more precisely. Our research in the past has focussed on the comparision of haptic and visual training for kinesthetic navigation tasks, and have found haptic training to be superior to visual training. This reiterates the significance of haptic feedback for a multitude of tasks, ranging from surgical training to patient rehabilitation.
Teleoperation and Human-Machine Systems
Human-Machine Interaction is another are we are interested in. For example, for coordinating Master/Slave Systems, which we created using the Barrett Robot Arm, we have exploited the continuous nonlinear integral feedback terms and Lyapunov-based techniques, despite the incomplete system knowledge.
