Traditionally pavement inspections are conducted using manually operated instruments, and hence are very labor-intensive. In this study, the authors propose the idea of using an autonomous robot to perform the pavement inspections, including for evenness and distress. Because inspection instruments are assumed to be mounted on the robot's platform, this robot is capable of inspecting pavement conditions while at the same time planning the upcoming motion path according to the inspection results. Working concurrently in this way significantly reduces the overall inspection time and amount of data to be stored. The authors propose four motion planning methods for robots: a transversal path planning method, a longitudinal path planning method, a random walk method, and an obstacle avoidance method. This paper presents the application of the motion planning methods to different pavement inspection tasks. It also illustrates the inspection process in a predefined inspection area, and in an inspection area that has random obstacles. The results of this research are suitable for use with a commercial robot to achieve the goal of robotic pavement inspections.