Detecting Water Hazards for Autonomous Off-Road Navigation

Detecting water hazards for autonomous, off-road navigation of unmanned ground vehicles is a largely unexplored problem. In this paper, we catalog environmental variables that affect the difficulty of this problem, including day vs. night operation, whether the water reflects sky or other terrain features, the size of the water body, and other factors. We briefly survey sensors that are applicable to detecting water hazards in each of these conditions. We then present analyses and results for water detection for four specific sensor cases: (1) using color image classification to recognize sky reflections in water during the day, (2) using ladar to detect the presence of water bodies and to measure their depth, (3) using short-wave infrared (SWIR) imagery to detect water bodies, as well as snow and ice, and (4) using mid-wave infrared (MWIR) imagery to recognize water bodies at night. For color imagery, we demonstrate solid results with a classifier that runs at nearly video rate on a 433 MHz processor. For ladar, we present a detailed propagation analysis that shows the limits of water body detection and depth estimation as a function of lookahead distance, water depth, and ladar wavelength. For SWIR and MWIR, we present sample imagery from a variety of data collections that illustrate the potential of these sensors. These results demonstrate significant progress on this problem. 1

Daytime Water Detection Based on Sky Reflections

Robust water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation. This is particularly true in wide-open areas where water can collect in naturally occurring terrain depressions during periods of heavy precipitation and form large water bodies. One of the properties of water useful for detecting it is that its surface acts as a horizontal mirror at large incidence angles. Water bodies can be indirectly detected by detecting reflections of the sky below the horizon in color imagery. The Jet Propulsion Laboratory (JPL) has implemented a water detector based on sky reflections that geometrically locates the pixel in the sky that is reflecting on a candidate water pixel on the ground and predicts if the ground pixel is water based on color similarity and local terrain features. This software detects water bodies in wide-open areas on cross-country terrain at mid- to far-range using imagery acquired from a forward-looking stereo pair of color cameras mounted on a terrestrial UGV. In three test sequences approaching a pond under a clear, overcast, and cloudy sky, the true positive detection rate was 100% when the UGV was beyond 7 meters of the water's leading edge and the largest false positive detection rate was 0.58%. The sky reflection based water detector has been integrated on an experimental unmanned vehicle and field tested at Ft. Indiantown Gap, PA, USA

Unmanned Ground Vehicle Perception Using Thermal Infrared Cameras

The ability to perform off-road autonomous navigation at any time of day or night is a requirement for some unmanned ground vehicle (UGV) programs. Because there are times when it is desirable for military UGVs to operate without emitting strong, detectable electromagnetic signals, a passive only terrain perception mode of operation is also often a requirement. Thermal infrared (TIR) cameras can be used to provide day and night passive terrain perception. TIR cameras have a detector sensitive to either mid-wave infrared (MWIR) radiation (3-5?m) or long-wave infrared (LWIR) radiation (8-12?m). With the recent emergence of high-quality uncooled LWIR cameras, TIR cameras have become viable passive perception options for some UGV programs. The Jet Propulsion Laboratory (JPL) has used a stereo pair of TIR cameras under several UGV programs to perform stereo ranging, terrain mapping, tree-trunk detection, pedestrian detection, negative obstacle detection, and water detection based on object reflections. In addition, we have evaluated stereo range data at a variety of UGV speeds, evaluated dual-band TIR classification of soil, vegetation, and rock terrain types, analyzed 24 hour water and 12 hour mud TIR imagery, and analyzed TIR imagery for hazard detection through smoke. Since TIR cameras do not currently provide the resolution available from megapixel color cameras, a UGV's daytime safe speed is often reduced when using TIR instead of color cameras. In this paper, we summarize the UGV terrain perception work JPL has performed with TIR cameras over the last decade and describe a calibration target developed by General Dynamics Robotic Systems (GDRS) for TIR cameras and other sensors

Mars Exploration Rovers 2004-2013: Evolving Operational Tactics Driven by Aging Robotic Systems

Over the course of more than 10 years of continuous operations on the Martian surface, the operations team for the Mars Exploration Rovers has encountered and overcome many challenges. The twin rovers, Spirit and Opportunity, designed for a Martian surface mission of three months in duration, far outlived their life expectancy. Spirit explored for six years and Opportunity still operates and, in January 2014, celebrated the 10th anniversary of her landing. As with any machine that far outlives its design life, each rover has experienced a series of failures and degradations attributable to age, use, and environmental exposure. This paper reviews the failures and degradations experienced by the two rovers and the measures taken by the operations team to correct, mitigate, or surmount them to enable continued exploration and discovery

Mars Science Laboratory Curiosity Rover Megaripple Crossings up to Sol 710 in Gale Crater

After landing in Gale Crater on August 6, 2012, the Mars Science Laboratory Curiosity rover traveled across regolith-covered, rock-strewn plains that transitioned into terrains that have been variably eroded, with valleys partially filled with windblown sands, and intervening plateaus capped by well-cemented sandstones that have been fractured and shaped by wind into outcrops with numerous sharp rock surfaces. Wheel punctures and tears caused by sharp rocks while traversing the plateaus led to directing the rover to traverse in valleys where sands would cushion wheel loads. This required driving across a megaripple (windblown, sand-sized deposit covered by coarser grains) that straddles a narrow gap and several extensive megaripple deposits that accumulated in low portions of valleys. Traverses across megaripple deposits led to mobility difficulties, with sinkage values up to approximately 30% of the 0.50 m wheel diameter, resultant high compaction resistances, and rover-based slip up to 77%. Analysis of imaging and engineering data collected during traverses across megaripples for the first 710 sols (Mars days) of the mission, laboratory-based single-wheel soil experiments, full-scale rover tests at the Dumont Dunes, Mojave Desert, California, and numerical simulations show that a combination of material properties and megaripple geometries explain the high wheel sinkage and slip events. Extensive megaripple deposits have subsequently been avoided and instead traverses have been implemented across terrains covered with regolith or thin windblown sand covers and megaripples separated by bedrock exposures