6,766 research outputs found
Perceiving Mass in Mixed Reality through Pseudo-Haptic Rendering of Newton's Third Law
In mixed reality, real objects can be used to interact with virtual objects.
However, unlike in the real world, real objects do not encounter any opposite
reaction force when pushing against virtual objects. The lack of reaction force
during manipulation prevents users from perceiving the mass of virtual objects.
Although this could be addressed by equipping real objects with force-feedback
devices, such a solution remains complex and impractical.In this work, we
present a technique to produce an illusion of mass without any active
force-feedback mechanism. This is achieved by simulating the effects of this
reaction force in a purely visual way. A first study demonstrates that our
technique indeed allows users to differentiate light virtual objects from heavy
virtual objects. In addition, it shows that the illusion is immediately
effective, with no prior training. In a second study, we measure the lowest
mass difference (JND) that can be perceived with this technique. The
effectiveness and ease of implementation of our solution provides an
opportunity to enhance mixed reality interaction at no additional cost
Research on real-time physics-based deformation for haptic-enabled medical simulation
This study developed a multiple effective visuo-haptic surgical engine to handle a variety of surgical manipulations in real-time. Soft tissue models are based on biomechanical experiment and continuum mechanics for greater accuracy. Such models will increase the realism of future training systems and the VR/AR/MR implementations for the operating room
Trajectory Deformations from Physical Human-Robot Interaction
Robots are finding new applications where physical interaction with a human
is necessary: manufacturing, healthcare, and social tasks. Accordingly, the
field of physical human-robot interaction (pHRI) has leveraged impedance
control approaches, which support compliant interactions between human and
robot. However, a limitation of traditional impedance control is that---despite
provisions for the human to modify the robot's current trajectory---the human
cannot affect the robot's future desired trajectory through pHRI. In this
paper, we present an algorithm for physically interactive trajectory
deformations which, when combined with impedance control, allows the human to
modulate both the actual and desired trajectories of the robot. Unlike related
works, our method explicitly deforms the future desired trajectory based on
forces applied during pHRI, but does not require constant human guidance. We
present our approach and verify that this method is compatible with traditional
impedance control. Next, we use constrained optimization to derive the
deformation shape. Finally, we describe an algorithm for real time
implementation, and perform simulations to test the arbitration parameters.
Experimental results demonstrate reduction in the human's effort and
improvement in the movement quality when compared to pHRI with impedance
control alone
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