M. Colin Marvin

Title: Surface Conditions on Titan from a Dune-Pattern Analysis

Abstract: Saturn's moon, Titan, is a sedimentary world like Earth and Mars. Observations from orbit reveal a geologically active surface with extensive fields of sand dunes. These dunes nearly encircle the equatorial regions, only interrupted by a mysterious terrain, Xanadu. Because dunes evolve in response to atmospheric and surface conditions, they offer a window into Titan's recent geologic and climate history. We conduct a global analysis of the patterns formed by dune crestlines. We find that dune spacing decreases continuously and the pattern becomes better organized along a pathway beginning at Xanadu's eastern margin, around the equator, terminating abruptly at Xanadu's western margin. These findings demonstrate that Titan's dune fields constitute a linked sedimentary system and that sand grains, previously hypothesized to be mechanically weak, must in fact withstand long travel distances.

Bio: I am a fourth-year PhD student in the Department of Earth and Planetary Sciences working with Prof. Mathieu Lapôtre. Before attending Stanford, I studied geography, GIS, and mathematics at Arizona State University. My research centers around Earth and planetary surface processes, with a specific focus in aeolian geomorphology. During my PhD, I have developed new quantitative frameworks to better understand aeolian systems and processes on dune fields throughout the Solar System. My work on dune patterns revealed that dunes retain a signature of environmental changes, which can be deciphered readily from satellite images of planetary surfaces.

Daniel Morton

Title: Enabling Robotic Manipulation in Martian Lava Tubes with ReachBot

Abstract: Recently, caves and lava tubes on celestial bodies like the Moon and Mars have emerged as areas of scientific interest due to their distinct geological and astrobiological characteristics, offering potential insights into the history of the solar system. Further exploration of these regions may uncover details about their past and future habitability, but this exploration is limited by the capabilities of existing robotic platforms, and their inability to access hard-to-reach locations. To address this need, ReachBot is a proposed robotic concept for enhanced mobility in challenging environments. Using deployable booms as reconfigurable prismatic joints, ReachBot can extend and traverse across large regions, accessing hard-to-reach areas of scientific interest. However, executing a manipulation task (for instance, sample extraction) in this environment is a challenging procedure with high uncertainty and disturbances which may cause a grasp failure. To address this, we develop a two-part planning solution, optimizing for robustness against task uncertainty and stochastic failure modes. First, we present a mixed-integer stance planner to determine the positioning of ReachBot's booms to maximize the task wrench space about the nominal point(s). Second, we present a convex tension planner to determine boom tensions for the desired task wrenches, accounting for the probabilistic nature of microspine grasping. Through this planner, we demonstrate improvements in key robustness metrics from the field of dexterous manipulation, show a large increase in the volume of the manipulation workspace, and achieve high success rates over a set of sampled tasks in randomized environments.

Bio: Daniel Morton is a PhD student in Mechanical Engineering, advised by Marco Pavone and co-advised by Mark Cutkosky. In the Autonomous Systems Lab, his research focuses on safe and efficient planning and control methods for robotic manipulation, with an emphasis on space and novel hardware platforms. Prior to Stanford, Daniel received his B.S. in Mechanical Engineering with an Aerospace minor from Cornell University, where he conducted research in the Organic Robotics Lab. Daniel has also interned at Boeing and NASA, and was an early member of a robotics startup, Medra. Outside of the lab, Daniel can be typically found on the tennis court or golf course, or skiing in Tahoe. https://stanfordasl.github.io/people/dan-morton/