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This paper introduces a novel approach for whole-body motion planning anddynamic occlusion avoidance. The proposed approach reformulates the visibilityconstraint as a likelihood maximization of visibility probability. In thisformulation, we augment the primary cost function of a whole-body modelpredictive control scheme through a relaxed log barrier function yielding arelaxed log-likelihood maximization formulation of visibility probability. Thevisibility probability is computed through a probabilistic shadow field thatquantifies point light source occlusions. We provide the necessary algorithmsto obtain such a field for both 2D and 3D cases. We demonstrate 2Dimplementations of this field in simulation and 3D implementations throughreal-time hardware experiments. We show that due to the linear complexity ofour shadow field algorithm to the map size, we can achieve high update rates,which facilitates onboard execution on mobile platforms with limitedcomputational power. Lastly, we evaluate the performance of the proposed MPCreformulation in simulation for a quadrupedal mobile manipulator.

Whole-Body MPC and Dynamic Occlusion Avoidance: A Maximum Likelihood Visibility Approach