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NASA NTRS1990

Planning for execution monitoring on a planetary rover

A planetary rover will be traversing largely unknown and often unknowable terrain. In addition to geometric obstacles such as cliffs, rocks, and holes, it may also have to deal with non-geometric hazards such as soft soil and surface breakthroughs which often cannot be detected until rover is in imminent danger. Therefore, the rover must monitor its progress throughout a traverse, making sure to stay on course and to detect and act on any previously unseen hazards. Its onboard planning system must decide what sensors to monitor, what landmarks to take position readings from, and what actions to take if something should go wrong. The planning systems being developed for the Pathfinder Planetary Rover to perform these execution monitoring tasks are discussed. This system includes a network of planners to perform path planning, expectation generation, path analysis, sensor and reaction selection, and resource allocation.

Gat, Erann↗

NASA NTRS2007

The Walkback Test: A Study to Evaluate Suit and Life Support System Performance Requirements for a 10 Kilometer Traverse in a Planetary Suit

As planetary suit and planetary life support systems develop, specific design inputs for each system relate to a presently unanswered question concerning operational concepts: What distance can be considered a safe walking distance for a suited EVA crew member exploring the surface of the Moon to "walk-back" to the habitat in the event of a rover breakdown, taking into consideration the planned EVA tasks as well as the possible traverse back to the habitat? It has been assumed, based on Apollo program experience, that 10 kilometers (6.2 mi) will be the maximum EVA excursion distance from the lander or habitat to ensure the crew member s safe return to the habitat in the event of a rover failure. To investigate the feasibility of performing a suited 10 km Walkback, NASA-JSC assembled a multi-disciplinary team to design and implement the Lunar Walkback Test . The test was designed not only to determine the feasibility of a 10 km excursion, but also to collect human performance, biomedical, and biomechanical data relevant to optimizing space suit design and life support system sizing. These data will also be used to develop follow-on studies to understand interrelationships of such key parameters as suit mass, inertia, suit pressure, and center of gravity (CG), and the respective influences of each on human performance.

Vos, Jessica R.↗

NASA NTRS2014

Comparing and Reconciling Traditional Field and Photogeologic Mapping Techniques: Lessons from the San Francisco Volcanic Field, Arizona

Cartographic products and - specifically - geologic maps provide critical assistance for establishing physical and temporal frameworks of planetary surfaces. The technical methods that result in the creation of geologic maps vary depending on how observations are made as well as the overall intent of the final products [1-3]. These methods tend to follow a common linear work flow, including the identification and delineation of spatially and temporally discrete materials (units), the documentation of their primary (emplacement) and secondary (erosional) characteristics, analysis of the relative and absolute age relationships between these materials, and the collation of observations and interpretations into an objective map product. The "objectivity" of a map is critical cross comparison with overlapping maps and topical studies as well as its relevance to scientific posterity. However, the "accuracy" and "correctness" of a geologic map is very subject to debate. This can be evidenced by comparison of existing geologic maps at various scales, particularly those compiled through field- and remote-based mapped efforts. Our study focuses on comparing the fidelity of (1) "Apollo-style" geologic investigations, where typically non-geologist crew members follow static traverse routes established through pre-mission planning, and (2) "traditional" field-based investigations, where geologists are given free rein to observe without preplanned routes. This abstract summarizes the regional geology wherein our study was conducted, presents the geologic map created from traditional field mapping techniques, and offers basic insights into how geologic maps created from different tactics can be reconciled in support of exploratory missions. Additional abstracts [4-6] from this study discuss various exploration and science results of these efforts.

Skinner, J. A., Jr.↗

NASA NTRSDate not supplied

The Gandalf Staff: A Mobile Tool for Lunar Exploration (2nd year of development)

The Gandalf Staff is a mobile tool designed to be a flexible device supporting crewed and uncrewed operations on the lunar surface. The core of the device is a 24v battery with communications and data storage systems. Initial optional components supporting crewed Extra-Vehicular Activity (EVA) include a LiDAR and 360˚ camera. These provide 3D mapping of the traverse for documentation, and to aid future planning. The mapping also creates outreach opportunities for the public to “stand beside” the astronaut in Virtual Reality (VR). The staff provides external lighting for field site illumination in the south polar region low sun angle environment. Navigation instruments for crew position determination with Lunar Search and Rescue (LunaSAR) are also included. The staff itself can be used as a walking aid or as a splint for Incapacitated Crew Rescue (ICR). As a stand-alone device, the staff operates as a long duration untended science platform collecting environmental data and sending it to a lunar base station. The stand-alone mode requires connection to an auxiliary power source (e.g. solar array) and energy storage system (e.g. battery), so it could become an electrical recharging station. To make rapid progress in the 1st year, and also to demonstrate innovative project management techniques, NASA guided a private industry partner, T STAR, in leading Capstone Engineering student teams at Texas A&M University (TAMU) for proof-of-concept development and testing. These teams developed the power system and demonstrated successful integration of LiDAR, WiFi communications, and external lighting subsystems. Another industry team at Jacobs Technology prototyped a tripod to hold the staff upright. For the 2nd year (FY’22), NASA will again collaborate with partners to prototype enhanced power and lighting concepts. Year 2 will also add new capability for LunaSAR and geophysical science instrumentation using a heat probe. The heat probe is based upon Apollo heritage but modified to measure subsurface volatile ice regimes at the Artemis landing site. Components of the Gandalf Staff can be developed, tested, and deployed independently, or on the integrated staff, rovers, or utility trailers. The project supports crew safety, lunar sample curation, mission science, and public outreach goals of NASA. PLAIN TEST SUMMARY: Gandalf Staff is a 24v battery powered mobile tool for the lunar surface supporting crewed geologic field site exploration, or as a stand-alone science platform. As a tool assisting astronauts conducting field geology, the Gandalf Staff provides external lighting to illuminate shadowed regions on the surface. It also documents the process of collecting rocks and dust samples using a LiDAR (laser range instrument) and cameras. The staff provides a beacon for emergency location of astronauts and augments communications when the astronauts are blocked by large boulders. As a standalone science platform, the Gandalf Staff provides a power system for instruments and sensors to measure the lunar environment over long periods of time. The staff gathers data and sends the results to a lunar base station for analysis.

External Lighting↗

NASA NTRSDate not supplied

Investigating the Applications of In-Situ Resource Utilization for Future Crewed Mars Missions

Several advancements are necessary before humans can safely explore Mars. One emerging strategy is In-Situ Resource Utilization (ISRU): the process of extracting raw materials found onsite and converting them into usable products to ensure a constant flow of vital resources and greatly reduce overall mission cost. Scientists must confirm the presence and accessibility of these resources for future crewed missions. Our team investigated the feasibility of ISRU in NE Syrtis, a region of Mars with varied geology, mineralogy, and hydrological history. NE Syrtis has abundant subsurface water and a diverse suite of mineral deposits including olivine, phyllosilicates, sulfates, and carbonates–all of which can be leveraged for fuel, medical supplies, and/or construction materials. We conceptualized a joint rover and helicopter expedition to analyze and sample these minerals over a two-year primary mission using Java Mission-planning and Analysis for Remote Sensing (JMARS), Planetary Data Systems (PDS), and Computer-Aided Design (CAD). We plotted a strategic traverse to regions of interest identified from remote sensing data and planned operations at each target. Our mission aimed to prepare for human presence on Mars by demonstrating the utility and viability of ISRU-focused operations.

Zahra M. Ronizi↗

NASA NTRS1977

The navigation system of the JPL robot

The control structure of the JPL research robot and the operations of the navigation subsystem are discussed. The robot functions as a network of interacting concurrent processes distributed among several computers and coordinated by a central executive. The results of scene analysis are used to create a segmented terrain model in which surface regions are classified by traversibility. The model is used by a path planning algorithm, PATH, which uses tree search methods to find the optimal path to a goal. In PATH, the search space is defined dynamically as a consequence of node testing. Maze-solving and the use of an associative data base for context dependent node generation are also discussed. Execution of a planned path is accomplished by a feedback guidance process with automatic error recovery.

Thompson, A. M.↗

NASA NTRS2004

Mars Exploration Rover Mission

Two rovers with a sophisticated geological payload have been operating on the surface of Mars since January of 2004. Future missions and their related technology developments will benefit from the lessons learned during these surface operations. The planning cycle was dictated by the communications opportunities and the times of day that the rovers could operate, and the team and tools were tuned to optimize the mission return for that cycle time. The ability to traverse and to approach and perform in situ investigations on targets was limited in speed by the same cycle time, due to required human involvement in the related planning and risk decisions. In addition traverse was limited by the speed of the on-board terrain and hazard assessment, and in situ operations were limited by a lack of autonomy. Different planning cycles and levels of autonomy should be considered for future surface missions, which will result in different approaches to science decision making.

Adler, M.↗

NASA NTRS1988

Robot path planning using a genetic algorithm

Robot path planning can refer either to a mobile vehicle such as a Mars Rover, or to an end effector on an arm moving through a cluttered workspace. In both instances there may exist many solutions, some of which are better than others, either in terms of distance traversed, energy expended, or joint angle or reach capabilities. A path planning program has been developed based upon a genetic algorithm. This program assumes global knowledge of the terrain or workspace, and provides a family of good paths between the initial and final points. Initially, a set of valid random paths are constructed. Successive generations of valid paths are obtained using one of several possible reproduction strategies similar to those found in biological communities. A fitness function is defined to describe the goodness of the path, in this case including length, slope, and obstacle avoidance considerations. It was found that with some reproduction strategies, the average value of the fitness function improved for successive generations, and that by saving the best paths of each generation, one could quite rapidly obtain a collection of good candidate solutions.

Cleghorn, Timothy F.↗

NASA NTRS2004

Autonomous Navigation Results from the Mars Exploration Rover (MER) Mission

In January, 2004, the Mars Exploration Rover (MER) mission landed two rovers, Spirit and Opportunity, on the surface of Mars. Several autonomous navigation capabilities were employed in space for the first time in this mission. ]n the Entry, Descent, and Landing (EDL) phase, both landers used a vision system called the, Descent Image Motion Estimation System (DIMES) to estimate horizontal velocity during the last 2000 meters (m) of descent, by tracking features on the ground with a downlooking camera, in order to control retro-rocket firing to reduce horizontal velocity before impact. During surface operations, the rovers navigate autonomously using stereo vision for local terrain mapping and a local, reactive planning algorithm called Grid-based Estimation of Surface Traversability Applied to Local Terrain (GESTALT) for obstacle avoidance. ]n areas of high slip, stereo vision-based visual odometry has been used to estimate rover motion, As of mid-June, Spirit had traversed 3405 m, of which 1253 m were done autonomously; Opportunity had traversed 1264 m, of which 224 m were autonomous. These results have contributed substantially to the success of the mission and paved the way for increased levels of autonomy in future missions.

autonomous↗

NASA NTRS2004

Learning to behave: adaptive behavior for planetary surface rovers

Robotic missions to planetary surfaces are becoming more ambitious and of longer duration. The nominal mission timeline for the MER called Spirit currently on the Martian surface is 90 days, with extensions to 180 days depending on rover health. The upcoming 2009 MSL mission is planned to be 300-500 days and will possibly involve traverses on the order of a kilometer or more.

autonomous robots↗

NASA NTRS2005

Domain Compilation for Embedded Real-Time Planning

A recently conceived approach to automated real-time control of the actions of a robotic system enables an embedded real-time planning algorithm to develop plans that are more robust than they would otherwise be, without imposing an excessive computational burden. This approach occupies a middle ground between two prior approaches known in the art as the universal-plan and hybrid approaches. Ever since discovering the performance limitations of taking a sense-plan-act approach to controlling robots, the robotics community has endeavored to follow a behavior-based approach in which a behavior includes a rapid feedback loop between state estimation and motor control. Heretofore, system architectures following this approach have been based, variously, on algorithms that implement universal plans or algorithms that function as hybrids of planners and executives. In a typical universal-plan case, a set of behaviors is merged into the plan, but the system must be restricted to relatively small problem domains to avoid having to reason about too many states and represent them in the plan. In the hybrid approach, one implements actions as small sets of behaviors, each applicable to a limited set of circumstances. Each action is intended to bring the system to a subgoal state. A planning algorithm is used to string these actions together into a sequence to traverse the state space from an initial or current state to a goal state. The hybrid approach works well in a static environment, but it is inherently brittle in a dynamic environment because a failure can occur when the environment strays beyond the region of applicability of the current activity. In the present approach, a system can vary from the hybrid approach to the universal-plan approach, depending on a single integer parameter, denoted n, which can range from 1 to a maximum domain-dependent value of M. As illustrated in the figure, n = 1 represents the hybrid approach, in which each linked action covers a small part of the state space of the system. As n increases, the portion of state space associated with each action and its subgoal grows. When n reaches M, coverage extends over the full state space, so that the system contains a universal plan.

Barrett, Anthony↗

NASA NTRS2003

Learning and planning for Mars Rover science

In this paper, we describe the OASIS system, which provides autonomous capabilities for dynamically pursuing these science-collection opportunities during long-range rover traverses.

data analysis planning autonomous rover operations↗

NASA NTRS1996

Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the GP model which in turn produces the pre-schedule of the optimal control model. Some preliminary results based on a hypothetical test case will be presented for the load forecasting module. The computer codes for the three modules will be made available fe adoption by bus operating agencies. Sample results will be provided using these models. The software will be a useful tool for supporting the control systems for the Electric Bus project of NASA.

Momoh, James↗

NASA NTRS2000

Rovers as Geological Helpers for Planetary Surface Exploration

Rovers can be used to perform field science on other planetary surfaces and in hostile and dangerous environments on Earth. Rovers are mobility systems for carrying instrumentation to investigate targets of interest and can perform geologic exploration on a distant planet (e.g. Mars) autonomously with periodic command from Earth. For nearby sites (such as the Moon or sites on Earth) rovers can be teleoperated with excellent capabilities. In future human exploration, robotic rovers will assist human explorers as scouts, tool and instrument carriers, and a traverse "buddy". Rovers can be wheeled vehicles, like the Mars Pathfinder Sojourner, or can walk on legs, like the Dante vehicle that was deployed into a volcanic caldera on Mt. Spurr, Alaska. Wheeled rovers can generally traverse slopes as high as 35 degrees, can avoid hazards too big to roll over, and can carry a wide range of instrumentation. More challenging terrain and steeper slopes can be negotiated by walkers. Limitations on rover performance result primarily from the bandwidth and frequency with which data are transmitted, and the accuracy with which the rover can navigate to a new position. Based on communication strategies, power availability, and navigation approach planned or demonstrated for Mars missions to date, rovers on Mars will probably traverse only a few meters per day. Collecting samples, especially if it involves accurate instrument placement, will be a slow process. Using live teleoperation (such as operating a rover on the Moon from Earth) rovers have traversed more than 1 km in an 8 hour period while also performing science operations, and can be moved much faster when the goal is simply to make the distance. I will review the results of field experiments with planetary surface rovers, concentrating on their successful and problematic performance aspects. This paper will be accompanied by a working demonstration of a prototype planetary surface rover.

Stoker, Carol↗

NASA NTRS1990

Planning strategies for the Ambler walking robot

A hierarchy of planning strategies is proposed and explained for a walking robot called the Ambler. The hierarchy decomposes planning into levels of trajectory, gait, and footfall. An abstraction of feasible traversability allows the Ambler's trajectory planner to identify acceptable trajectories by finding paths that guarantee footfalls without specifying exactly which footfalls. Leg and body moves that achieve this trajectory can be generated by the Ambler's gait planner, which incorporates pattern constraints and measures of utility to search for the best next move. By combining constraints from the quality and details of the terrain, the Ambler's footfall planner can select footfalls that insure stability and remain within the tolerances of the gait.

Wettergreen, David↗

NASA NTRS1991

A six-legged rover for planetary exploration

To survive the rigors and isolation of planetary exploration, an autonomous rover must be competent, reliable, and efficient. This paper presents the Ambler, a six-legged robot featuring orthogonal legs and a novel circulating gait, which has been designed for traversal of rugged, unknown environments. An autonomous software system that integrates perception, planning, and real-time control has been developed to walk the Ambler through obstacle strewn terrain. The paper describes the information and control flow of the walking system, and how the design of the mechanism and software combine to achieve competent walking, reliable behavior in the face of unexpected failures, and efficient utilization of time and power.

Simmons, Reid↗

NASA NTRS2021

Framework for Coordinated Efforts in the Exploration of Volatiles in the South Polar Region of the Moon

The exploration of the lunar south polar region and the ground truthing of polar volatiles is one of the top priorities for several space agencies and private partners. Here we use Moon Mineralogy Mapper surficial water ice detections to investigate the location of water ice-bearing permanently shaded regions near the south pole. We extract a variety of parameters such as their temperature regime, slope, hydrogen content, number of ice detections, depth stability for water ice and dry ice, and mobility aspects. We identify 169 water ice-bearing PSRs and use their characteristics to identify sites that allow to access the highest abundances of volatiles, sites that can be visited to characterize the lateral or vertical distribution of volatiles (water ice and dry ice), and sites that allow for the fastest recovery of a scientifically interesting sample. Collectively, 37 PSRs are identified as sites of interest, including 11 that would address more than one mission objective and may be, for that reason, higher priority targets of exploration. These PSRs are found in Shoemaker, Faustini, Cabeus, Malapert, Nobile, Sverdrup, Wiechert J and Haworth craters, as well as 3 unnamed craters (PSRs 57, 120, 89). These sites are all located within 6 degrees of the south pole. We present case studies for a relatively short traverse mission (20 to 50 km) to PSR 89, a medium length traverse (~100 km) to Sverdrup 1, and a longer traverse (~300 km) to Cabeus that can serve as a guide in planning upcoming exploration missions.

Myriam Lemelin↗

NASA NTRS2021

Machine Learning Based Path Planning for Improved Rover Navigation

Enhanced AutoNav (ENav), the baseline surface navigation software for NASA’s Perseverance rover, sorts a list of candidate paths for the rover to traverse, then uses the Approximate Clearance Evaluation (ACE) algorithm to evaluate whether the most highly ranked paths are safe. ACE is crucial for maintaining the safety of the rover, but is computationally expensive. If the most promising candidates in the list of paths are all found to be infeasible, ENav must continue to search the list and run time-consuming ACE evaluations until a feasible path is found. In this paper, we present two heuristics that, given a terrain heightmap around the rover, produce cost estimates that more effectively rank the candidate paths before ACE evaluation. The first heuristic uses Sobel operators and convolution to incorporate the cost of traversing high-gradient terrain. The second heuristic uses a machine learning (ML) model to predict areas that will be deemed untraversable by ACE. We used physics simulations to collect training data for the ML model and to run Monte Carlo trials to quantify navigation performance across a variety of terrains with various slopes and rock distributions. Compared to ENav's baseline performance, integrating the heuristics can lead to a significant reduction in ACE evaluations and average computation time per planning cycle, increase path efficiency, and maintain or improve the rate of successful traverses. This strategy of targeting specific bottlenecks with ML while maintaining the original ACE safety checks provides an example of how ML can be infused into planetary science missions and other safety-critical software.

Yue, Yisong↗