Daytime Mud Detection for Unmanned Ground Vehicle Autonomous Navigation

摘要

Detecting mud hazards is a significant challenge to UGV autonomous off-road navigation. A military UGV stuck in a mud body during a mission may need to be sacrificed or rescued, both unattractive options. JPL is currently developing a daytime mud detection capability under the RCTA program using UGV mounted sensors. To perform robust mud detection under all conditions, we expect multiple sensors will be necessary. A passive mud detection solution is desirable to meet the FCS-ANS requirements. To characterize the advantages and disadvantages of candidate passive sensors, data collections have been performed on wet and dry soil using visible, multi-spectral (including near- infrared), shortwave infrared, mid-wave infrared, long-wave infrared, polarization, and stereo sensors. In this paper, we examine the cues for mud detection each of these sensors provide, along with their deficiencies, and we illustrate localizing detected mud in a world model that can used by a UGV to plan safe paths.