Point clouds can be represented as implicit surfaces for constraint-based haptic rendering

We present a constraint-based strategy for haptic rendering of arbitrary point cloud data. With the recent proliferation of low-cost range sensors, dense 3D point cloud data is readily available at high update rates. Taking a cue from the graphics literature, we propose that point data should be represented as an implicit surface, which can be formulated to be mathematically smooth and efficient for computing interaction forces, and for which haptic constraint algorithms are already well-known. This method is resistant to sensor noise, makes no assumptions about surface connectivity or orientation, and data pre-processing is fast enough for use with streaming data. We compare the performance of two different implicit representations and discuss our strategy for handling time-varying point clouds from a depth camera. Applications of haptic point cloud rendering to remote sensing, as in robot telemanipulation, are also discussed.