Visual information is heavily used in robotics, in particular for SLAM applications. Visual SLAM algorithms depend on robust feature extraction and reliable state estimation. Quality of the visual information highly depends on how that information is captured. The nature of snake robots’ locomotion presents considerable challenges on the quality of images captured by an onboard mobile camera. Although placing the camera on the “head” of the snake robot has advantages when the robot is stationary since the body can be used as a manipulator observing for the environment, how to place the camera in order to capture more useful images for navigation during locomotion is not clear. In this paper, we present a comparative study to discuss implications of the camera location on field coverage and types of image quality for three snake gaits: Rolling, sidewinding and linear progression. Camera pose during locomotion is examined in detail and quality of images are quantified using a motion blur metric which relates camera egomotion to blur. Linear progression is found to be very promising in terms of supplying sharper images. But, there are also other merits that can be exploited in different locomotion types and camera locations.