Path planning and navigation inside off-world lava tubes and caves

Abstract

Detailed surface images of the Moon and Mars reveal hundreds of cave-like openings. These cave-like openings are theorized to be remnants of lava-tubes and their interior maybe in pristine conditions. These locations may have well preserved geological records of the Moon and Mars, including evidence of past water flow and habitability. Exploration of these caves using wheeled rovers remains a daunting challenge. These caves are likely to have entrances with caved-in ceilings much like the lava-tubes of Arizona and New Mexico. Thus, the entrances are nearly impossible to traverse even for experienced human hikers. Our approach is to utilize the SphereX robot, a 3 kg, 30 cm diameter robot with computer hardware and sensors of a smartphone attached to rocket thrusters. Each SphereX robot can hop, roll or fly short distances in low gravity, airless or lowpressure environments. Several SphereX robots maybe deployed to minimize single-point failure and exploit cooperative behaviors to traverse the cave. There are some important challenges for navigation and path planning in these cave environments. Localization systems such as GPS are not available nor are they easy to install due to the signal blockage from the rocks. These caves are too dark and too large for conventional sensor such as cameras and miniature laser sensors to perform detailed mapping and navigation. In this paper, we identify new techniques to map these caves by performing localized, cooperative mapping and navigation. In our approach, a team of SphereX robots much like a team of cave explorer will adopt specialized roles to perform navigation. For a minimal science mission, these robots need to obtain camera images and basic maps of the cave interior to be transmitted back to a lander or rover situated outside the cave. The teams of SphereX robots form a bucket brigade and partition the currently accessible volume of the cave. Then the teams of robots attempt to expand their reach deeper into the cave and sense their progress. Imaging the cave interior is expensive and require use of high-power strobe lights. The images would be compiled into a 3D point cloud and meshed by the lander or transmitted to ground. Using this conservative approach, we ensure the robots are always within communication reach of a lander/rover outside the cave. Once large segments of the cave are mapped, the rovers may lay down a network of mirrors to beam sunlight and laser light from a base station at the cave entrance to the far reaches of the cave. These mirrors also help the robots identify a pathway back to the cave entrance. Efforts are underway to perform field experiments to validate the feasibility our proposed approach to cave exploration.

Strategies for Deploying a Sensor Network to Explore Planetary Lava Tubes

“…The SphereX robots will then hop near the pit entrance, enter the pit and start mapping using the onboard 3D LiDAR sensors and stereo cameras. The robots would act as a communications relay by forming bucket brigades [ 34 ] and allowing exploration of areas with vertical overhangs, such as pits and lava tubes. The lander will serve as the main communications relay to Earth and would have instruments such as a science camera to observe the descent and the vicinity around the landing.…”

Interiors of small bodies and moons

“…Looking deeper, bodies up to the size of Phobos have central pressures of less than 1 bar, so if they are made of rubble or have fissures, then a burrowing robot could explore the deep interior, assuming engineers can figure out power, communication and thermal problems. Using more traditional technologies, robots can thread their way through caverns and interconnected voids 16 , and even cometary vents, the way they will investigate skylights into lava tubes on the nearside of the Moon (Fig. 2b).…”

STEP: Stochastic Traversability Evaluation and Planning for Risk-Aware Off-road Navigation

“…rubble, slopes) and non-forgiving hazards (e.g. large drops, sharp rocks) (See Figure 1) [22]. Determining where the robot may safely travel is a non-trivial problem, compounded by several issues: 1) Localization error affects how sensor measurements are accumulated to generate dense maps of the environment.…”