  UV radiation has been used as a disinfection strategy to deactivate a wide
range of pathogens, but existing irradiation strategies do not ensure
sufficient exposure of all environmental surfaces and/or require long
disinfection times. We present a near-optimal coverage planner for mobile UV
disinfection robots. The formulation optimizes the irradiation time efficiency,
while ensuring that a sufficient dosage of radiation is received by each
surface. The trajectory and dosage plan are optimized taking collision and
light occlusion constraints into account. We propose a two-stage scheme to
approximate the solution of the induced NP-hard optimization, and, for
efficiency, perform key irradiance and occlusion calculations on a GPU.
Empirical results show that our technique achieves more coverage for the same
exposure time as strategies for existing UV robots, can be used to compare UV
robot designs, and produces near-optimal plans. This is an extended version of
the paper originally contributed to ICRA2021.
