The Holy Grail: A road map for unlocking the climate record stored within Mars' polar layered deposits

In its polar layered deposits (PLD), Mars possesses a record of its recent climate, analogous to terrestrial ice sheets containing climate records on Earth. Each PLD is greater than 2 ​km thick and contains thousands of layers, each containing information on the climatic and atmospheric state during its deposition, creating a climate archive. With detailed measurements of layer composition, it may be possible to extract age, accumulation rates, atmospheric conditions, and surface activity at the time of deposition, among other important parameters; gaining the information would allow us to “read” the climate record. Because Mars has fewer complicating factors than Earth (e.g. oceans, biology, and human-modified climate), the planet offers a unique opportunity to study the history of a terrestrial planet’s climate, which in turn can teach us about our own planet and the thousands of terrestrial exoplanets waiting to be discovered. During a two-part workshop, the Keck Institute for Space Studies (KISS) hosted 38 Mars scientists and engineers who focused on determining the measurements needed to extract the climate record contained in the PLD. The group converged on four fundamental questions that must be answered with the goal of interpreting the climate record and finding its history based on the climate drivers. The group then proposed numerous measurements in order to answer these questions and detailed a sequence of missions and architecture to complete the measurements. In all, several missions are required, including an orbiter that can characterize the present climate and volatile reservoirs; a static reconnaissance lander capable of characterizing near surface atmospheric processes, annual accumulation, surface properties, and layer formation mechanism in the upper 50 ​cm of the PLD; a network of SmallSat landers focused on meteorology for ground truth of the low-altitude orbiter data; and finally, a second landed platform to access ~500 ​m of layers to measure layer variability through time. This mission architecture, with two landers, would meet the science goals and is designed to save costs compared to a single very capable landed mission. The rationale for this plan is presented below. In this paper we discuss numerous aspects, including our motivation, background of polar science, the climate science that drives polar layer formation, modeling of the atmosphere and climate to create hypotheses for what the layers mean, and terrestrial analogs to climatological studies. Finally, we present a list of measurements and missions required to answer the four major questions and read the climate record. 1. What are present and past fluxes of volatiles, dust, and other materials into and out of the polar regions? 2. How do orbital forcing and exchange with other reservoirs affect those fluxes? 3. What chemical and physical processes form and modify layers? 4. What is the timespan, completeness, and temporal resolution of the climate history recorded in the PLD

Report of the Terrestrial Bodies Science Working Group. Volume 5: Mars

Present knowledge of the global properties and surface characteraretics of Mars and the composition and dynamics of its atmosphere are reviewed. The objectives of proposed missions, the exploration strategy, and supporting research and technology required are delineated

Space exploration: The interstellar goal and Titan demonstration

Automated interstellar space exploration is reviewed. The Titan demonstration mission is discussed. Remote sensing and automated modeling are considered. Nuclear electric propulsion, main orbiting spacecraft, lander/rover, subsatellites, atmospheric probes, powered air vehicles, and a surface science network comprise mission component concepts. Machine, intelligence in space exploration is discussed

Automated Image Interpretation for Science Autonomy in Robotic Planetary Exploration

Advances in the capabilities of robotic planetary exploration missions have increased the wealth of scientific data they produce, presenting challenges for mission science and operations imposed by the limits of interplanetary radio communications. These data budget pressures can be relieved by increased robotic autonomy, both for onboard operations tasks and for decision- making in response to science data. This thesis presents new techniques in automated image interpretation for natural scenes of relevance to planetary science and exploration, and elaborates autonomy scenarios under which they could be used to extend the reach and performance of exploration missions on planetary surfaces. Two computer vision techniques are presented. The first is an algorithm for autonomous classification and segmentation of geological scenes, allowing a photograph of a rock outcrop to be automatically divided into regions by rock type. This important task, currently performed by specialists on Earth, is a prerequisite to decisions about instrument pointing, data triage, and event-driven operations. The approach uses a novel technique to seek distinct visual regions in outcrop photographs. It first generates a feature space by extracting multiple types of visual information from the image. Then, in a training step using labeled exemplar scenes, it applies Mahalanobis distance metric learning (in particular, Multiclass Linear Discriminant Analysis) to discover the linear transformation of the feature space which best separates the geological classes. With the learned representation applied, a vector clustering technique is then used to segment new scenes. The second technique interrogates sequences of images of the sky to extract, from the motion of clouds, the wind vector at the condensation level — a measurement not normally available for Mars. To account for the deformation of clouds and the ephemerality of their fine-scale features, a template-matching technique (normalized cross-correlation) is used to mutually register images and compute the clouds’ motion. Both techniques are tested successfully on imagery from a variety of relevant analogue environments on Earth, and on data returned from missions to the planet Mars. For both, scenarios are elaborated for their use in autonomous science data interpretation, and to thereby automate certain steps in the process of robotic exploration

Human and Robotic Mission to Small Bodies: Mapping, Planning and Exploration

This study investigates the requirements, performs a gap analysis and makes a set of recommendations for mapping products and exploration tools required to support operations and scientific discovery for near- term and future NASA missions to small bodies. The mapping products and their requirements are based on the analysis of current mission scenarios (rendezvous, docking, and sample return) and recommendations made by the NEA Users Team (NUT) in the framework of human exploration. The mapping products that sat- isfy operational, scienti c, and public outreach goals include topography, images, albedo, gravity, mass, density, subsurface radar, mineralogical and thermal maps. The gap analysis points to a need for incremental generation of mapping products from low (flyby) to high-resolution data needed for anchoring and docking, real-time spatial data processing for hazard avoidance and astronaut or robot localization in low gravity, high dynamic environments, and motivates a standard for coordinate reference systems capable of describing irregular body shapes. Another aspect investigated in this study is the set of requirements and the gap analysis for exploration tools that support visualization and simulation of operational conditions including soil interactions, environment dynamics, and communications coverage. Building robust, usable data sets and visualisation/simulation tools is the best way for mission designers and simulators to make correct decisions for future missions. In the near term, it is the most useful way to begin building capabilities for small body exploration without needing to commit to specific mission architectures

Autonomous Systems, Robotics, and Computing Systems Capability Roadmap: NRC Dialogue

Contents include the following: Introduction. Process, Mission Drivers, Deliverables, and Interfaces. Autonomy. Crew-Centered and Remote Operations. Integrated Systems Health Management. Autonomous Vehicle Control. Autonomous Process Control. Robotics. Robotics for Solar System Exploration. Robotics for Lunar and Planetary Habitation. Robotics for In-Space Operations. Computing Systems. Conclusion