  This paper introduces a novel approach for whole-body motion planning and
dynamic occlusion avoidance. The proposed approach reformulates the visibility
constraint as a likelihood maximization of visibility probability. In this
formulation, we augment the primary cost function of a whole-body model
predictive control scheme through a relaxed log barrier function yielding a
relaxed log-likelihood maximization formulation of visibility probability. The
visibility probability is computed through a probabilistic shadow field that
quantifies point light source occlusions. We provide the necessary algorithms
to obtain such a field for both 2D and 3D cases. We demonstrate 2D
implementations of this field in simulation and 3D implementations through
real-time hardware experiments. We show that due to the linear complexity of
our shadow field algorithm to the map size, we can achieve high update rates,
which facilitates onboard execution on mobile platforms with limited
computational power. Lastly, we evaluate the performance of the proposed MPC
reformulation in simulation for a quadrupedal mobile manipulator.
