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Fat Man underwater propulsion vehicle ENDURANCE lands at Lake Bonney, Antarctica
Variable depth underwater habitat DEPTHX testing at the Applied Research Lab at UT
Bill Stone reads a paperback while spending 24 hours underwater using the MK1 rebreather Map of Wakulla Springs created using the Digital Wall Mapper MK1 rebreather
DEPTHX (DEep Phreatic THermal eXplorer)

During the past six years Stone Aerospace has developed two generations of autonomous underwater vehicles and used them in a wide variety of hazardous environments from the original exploration and mapping of deep hydrothermal springs to sub-glacial lake exploration and science missions in Antarctica. The first of these vehicles - DEPTHX (DEep Phreatic THermal eXplorer) - was designed to test the ability of a mobile robotic platform to autonomously explore and map in 3D where no external navigation aiding is possible and where no prior map data exists, as part of NASA planetary robotic efforts directed towards enabling a future mission to the sub-surface ocean of Europa, the 4th moon of Jupiter. DEPTHX broke new ground on several fronts:

  • First mobile robotic system of any kind to implement 3D-SLAM (Simultaneous Localization And Mapping) as part of a real-time navigation engine.
  • First autonomous robotic system to explore and map a subterranean cavern (a hydrothermal spring).
  • First robotic system to autonomously decide where, when and how to collect a biological sample.

The patent-pending DEPTHX design is shown in Figures 1, 2, 3, and 4. It was designed for survivability and precision maneuvering capability in 3D space. The external geometry is an axi-symmetric ellipsoid of revolution, which eliminates snag points in unknown and cluttered environments. It also allows the vehicle to be "spun up" in autonomous mode with very low energy. This technique, combined with high-resolution sonar imaging systems and precision navigation allows for dense geo-registered 3D maps to be rapidly generated in unknown environments. It is this dense 3D point cloud that serves as the feedstock to the 3D-SLAM navigation engine described below.


Figure 1: DepthX AUV in the assembled configuration. The vehicle was designed to have a significant vertical differential between the center of mass and the center of buoyancy. This provides resistance to dynamic sway and permits the vehicle to be dynamically modeled as an uncoupled 4 DOF system.


Figure 2: Vehicle-centric coordinate system for the DepthX AUV. The vehicle is ellipsoidal with a major axis of 2 m, a minor axis of 1.5 m and a mass of 1.35 metric tonnes. It contains a large central payload bay for rack mounted tools, instruments, and autonomous sub-systems.


Figure 3: Vertical module design. This allows for vertical assembly of the vehicle as well as the operation of all electronics in their assembled configuration with the pressure housings removed. The extensible science probe retracts flush with the vehicle ellipsoid during normal transit and exploration operations.


Figure 4: 3D SLAM sonar arrays. These form an integral part of the DepthX navigation architecture.

Navigation Systems

DEPTHX was unusual in the world of autonomous undersea devices in that it actively controlled precise motion in all 4 degrees of freedom (X,Y,Z, and yaw, with pitch and roll intentionally damped to provide vehicle precision stability for instrument pointing).

DEPTHX used two independent navigation systems. The high-grade dead reckoning system used an inertial reference unit and ring laser gyro, a redundant pair of depth sensors, and a doppler velocity log. This instrument collection, combined with onboard custom code and Kalman filter, demonstrated long range open loop control on the order of 0.05 to 0.1 % of distance traveled (less than 1 meter of error per kilometer of traverse). The second navigation engine was 3D-SLAM. Aside from making the vehicle survivable, the ellipsoidal shape and the exoskeleton frame were driven by the sensor architecture needed to implement 3D SLAM. The vehicle is literally an all-seeing eyeball, with tight beam sensors pointing in all directions (Figure 5). Using forward and backward-looking range sensors and very sophisticated real-time mathematics, DEPTHX can locate itself within a geometric environment, even one that it just explored for the first time only seconds previously. The 3D-SLAM accuracy on DEPTHX is approximately 1 meter anywhere within a 500-meter cube about the vehicle. Figures 6a-e shows the steps involved: the 3D map is created during the exploration process (6a); but the map has noise (6b); probabilistic sensor models are used to discriminate between what is real and what is noise (6c); and after several iterations a noise-free, feature-rich 3D model is achieved (6d); finally, the vehicle determines, through a computationally intense phase, an estimate of its position and orientation that produces the least error with the current 3D map (6e). This combined navigation system (dead reckoning and 3DSLAM) enabled the autonomous original exploration of the Zacatón hydrothermal spring complex in Mexico in the spring of 2007 (see Figures 7 and 8).


Figure 5: Acoustic view of the 4-π steradian tight-beam sonar array.


Figure 6: World's first implementation of 3D-SLAM. SLAM was tested as part of the DepthX navigation engine at the Zacatón hydrothermal spring complex in northern Mexico, May 2007. 6a) 3D point cloud map generated at the 105 meter deep Cenote La Pilita; 6b) 10-meter horizontal slice through the La Pilita data set showing sonar noise; 6c) acoustic beam physics 3D transducer dispersion model; 6d) 3D oblique view of the 3D probability map generated by the SLAM engine for the same locus as 6b following several localization iterations; 6e) 3D evidence map with the highest probability vehicle location plotted, red cones represent current valid return sonar beam models.


Figures 7a-c: 2007 DepthX mission to the Zacatón hydrothermal spring complex. At these previously unexplored hydrothermal vents, DepthX autonomously explored and mapped the chemically rich, hot water cenotes, to a depth of 319 meters in the case of Cenote Zacatón.


Figure 8: 3D maps of the cenotes. During three months of fieldwork in the spring of 2007, DepthX produced 3D underwater maps for all four of the major hydrothermal springs of the Zacatón complex. Laser radar data (above water) were merged with the geo-registered underwater data to form the composite image shown. All exploration was accomplished autonomously with no human guidance once a mission was begun.

DepthX Science Package

DepthX's science payload consists of a water and rock core sampling system that extends 1.5 meters from the vehicle in hazardous wall proximity zones (see Figures 9a-c) and which can be used to extract rock samples to depths of 1,000 meters.


Figure 9: DepthX Science Payload. An autonomous science program was conducted at Cenote Zacatón where an extendable probe (9a, 9b) collected water samples from the cenote and rock core samples from the wall of the cenote. The local probe camera captured the image shown in 9c, during which a core was extracted from the wall of the cenote at -273 meters. (See video of this.) This and other such samples were acquired automatically by the robot, operating under its own criteria. The highlight of this was a May 26, 2007 mission in which the vehicle was instructed to autonomously explore down into the cenote seeking chemoclines and, if it found such a layer, to select the safest approach to a wall and to collect a core at that location. The samples collected during these missions have since led to the discovery of six new Divisions of bacteria, when less than one hundred were previously known on Earth.

For more information on DEPTHX please see our daily updates from the field in Tamaulipas, Mexico.

Contact our engineering staff for further information.