The performance of a mobile sensor can be greatly improved by planning its path with respect to its sensing objective, field-of-view, and platform geometry. Although many algorithms have been developed for the related field of robot path planning, a majority of these methodologies cannot be directly applied to the problem of sensor path planning. This paper presents a technique by which mixed-integer programming (MIP) can be used to determine the optimal path of a mobile sensor. MIP is able to return solutions in non-convex environments, and has a flexible framework that allows for the consideration of vehicle dynamics, obstacle avoidance, and, as shown here, target measurement objectives. The primary contribution of this work is the development of a poof of the duality of robot and sensor path planning. By use of MIP, the proof shows that many approaches to classical robot navigation problems can be reformulated for sensor path planning. Illustrative simulation results for the paths of mobile robots and sensor platforms are presented; MATLAB and Tomlab/CPLEX were used to solve the path optimization problems.