Point cloud registration (PCR) can significantly
extend the visual field and enhance the point density on distant
objects, thereby improving driving safety. However, it is very
challenging for vehicles to perform online registration between
long-range point clouds. In this paper, we propose an online
long-range PCR scheme in VANETs, called LoRaPCR, where
vehicles achieve long-range registration through multi-hop short-
range highly-accurate registrations. Given the NP-hardness of the
problem, a heuristic algorithm is developed to determine best reg-
istration paths while leveraging the reuse of registration results
to reduce computation costs. Moreover, we utilize an optimized
dynamic programming algorithm to determine the transmission
routes while minimizing the communication overhead. Results
of extensive simulations demonstrate that LoRaPCR can achieve
high PCR accuracy with low relative translation and rotation
errors of 0.55 meters and 1.43◦, respectively, at a distance of
over 100 meters, and reduce the computation overhead by more
than 50% compared to the state-of-the-art method.

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