Kavli Affiliate: Cheng Peng
| First 5 Authors: Cheng Peng, Minghan Wei, Volkan Isler, ,
| Summary:
We introduce a new route-finding problem which considers perception and
travel costs simultaneously. Specifically, we consider the problem of finding
the shortest tour such that all objects of interest can be detected
successfully. To represent a viable detection region for each object, we
propose to use an entropy-based viewing score that generates a diameter-bounded
region as a viewing neighborhood. We formulate the detection-based trajectory
planning problem as a stochastic traveling salesperson problem with
neighborhoods and propose a center-visit method that obtains an approximation
ratio of O(DmaxDmin) for disjoint regions. For non-disjoint regions, our method
-provides a novel finite detour in 3D, which utilizes the region’s minimum
curvature property. Finally, we show that our method can generate efficient
trajectories compared to a baseline method in a photo-realistic simulation
environment.
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