Autonomous Trail Following

Trails typically lack standard markers that characterize roadways. Nevertheless, trails are useful for off-road navigation. Here, trail following problem is approached by identifying the deviation of the robot from the heading direction of the trail by fine-tuning a pre-trained Inception-V3 [1] network. Key questions considered in this work include the required number, nature and geometry of the cameras and how trail types -- encoded in pre-existing maps -- can be exploited in addressing this task. Through evaluation of representative image datasets and on-robot testing we found: (i) that although a single camera cannot estimate angular deviation from the heading direction, but it can reliably detect that the robot is, or is not, following the trail; (ii) that two cameras pointing towards the left and the right can be used to estimate heading reliably within a differential framework; (iii) that trail nature is a useful tool for training networks for different trail types.