The Mars Curiosity Rover Mission: Remotely Operating a Science Laboratory on the Surface of Another Planet
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science objective↗
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Real-Time Science Operations to Support a Lunar Polar Volatiles Rover Mission
Future human exploration of the Moon will likely rely on in situ resource utilization (ISRU) to enable long duration lunar missions. Prior to utilizing ISRU on the Moon, the natural resources (in this case lunar volatiles) must be identified and characterized, and ISRU demonstrated on the lunar surface. To enable future uses of ISRU, NASA and the CSA are developing a lunar rover payload that can (1) locate near subsurface volatiles, (2) excavate and analyze samples of the volatile-bearing regolith, and (3) demonstrate the form, extractability and usefulness of the materials. Such investigations are important both for ISRU purposes and for understanding the scientific nature of these intriguing lunar volatile deposits. Temperature models and orbital data suggest near surface volatile concentrations may exist at briefly lit lunar polar locations outside persistently shadowed regions. A lunar rover could be remotely operated at some of these locations for the approx. 2-14 days of expected sunlight at relatively low cost. Due to the limited operational time available, both science and rover operations decisions must be made in real time, requiring immediate situational awareness, data analysis, and decision support tools. Given these constraints, such a mission requires a new concept of operations. In this paper we outline the results and lessons learned from an analog field campaign in July 2012 which tested operations for a lunar polar rover concept. A rover was operated in the analog environment of Hawaii by an off-site Flight Control Center, a rover navigation center in Canada, a Science Backroom at NASA Ames Research Center in California, and support teams at NASA Johnson Space Center in Texas and NASA Kennedy Space Center in Florida. We find that this type of mission requires highly efficient, real time, remotely operated rover operations to enable low cost, scientifically relevant exploration of the distribution and nature of lunar polar volatiles. The field demonstration illustrated the need for science operations personnel in constant communications with the flight mission operators and the Science Backroom to provide immediate and continual science support and validation throughout the mission. Specific data analysis tools are also required to enable immediate data monitoring, visualization, and decision making. The field campaign demonstrated that this novel methodology of real-time science operations is possible and applicable to providing important new insights regarding lunar polar volatiles for both science and exploration.
Moon; Volatiles; Rover; Missions↗
Targeting and Localization for Mars Rover Operations
In this work we discuss how the quality of localization knowledge impacts the remote operation of rovers on the surface of Mars. We look at the techniques of localization estimation used in the Mars Pathfinder and Mars Exploration Rover missions. We examine the motivation behind the modes of targeting for different types of activities, such as navigation, remote science, and in situ science. We discuss the virtues and shortcomings of existing approaches and new improvements in the latest operations tools used to support the Mars Exploration Rover missions and rover technology development tasks at the Jet Propulsion Laboratory. We conclude with future directions we plan to explore in improving the localization knowledge available for operations and more effective targeting of rovers and their instrument payloads.
remote rover operations↗
A Simulated Geochemical Rover Mission to the Taurus-Littrow Valley of the Moon
We test the effectiveness of using an alpha backscatter, alpha-proton, X ray spectrometer on a remotely operated rover to analyze soils and provide geologically useful information about the Moon during a simulated mission to a hypothetical site resembling the Apollo 17 landing site. On the mission, 100 soil samples are "analyzed" for major elements at moderate analytical precision (e.g., typical relative sample standard deviation from counting statistics: Si[11%], Al[18%], Fe[6%], Mg[20%], Ca[5%]). Simulated compositions of soils are generated by combining compositions of components representing the major lithologies occurring at the site in known proportions. Simulated analyses are generated by degrading the simulated compositions according to the expected analytical precision of the analyzer. Compositions obtained from the simulated analyses are modeled by least squares mass balance as mixtures of the components, and the relative proportions of those components as predicted by the model are compared with the actual proportions used to generate the simulated composition. Boundary conditions of the modeling exercise are that all important lithologic components of the regolith are known and are represented by model components, and that the compositions of these components are well known. The effect of having the capability of determining one incompatible element at moderate precision (25%) is compared with the effect of the lack of this capability. We discuss likely limitations and ambiguities that would be encountered, but conclude that much of our knowledge about the Apollo 17 site (based on the return samples) regarding the distribution and relative abundances of lithologies in the regolith could be obtained. This success requires, however, that at least one incompatible element be determined.
Korotev, Randy L.↗
Resilience Modeling in Complex Engineered Systems with Human-Machine Interactions
In recent times, there has been a growing interest in resilience-based design. Resilience-based design operates on the concept that failures and unexpected events will happen, and when they occur, complex engineered systems should be able to operate within acceptable bounds and recover reasonably. Humans can contribute to the resilience of a system by quickly detecting unforeseen events and taking corrective measures. To this effect, researchers have proposed guidelines and design approaches that can help promote human-system resilience. However, there is no early design stage tool to validate if a system is indeed resilient after applying these guidelines and design methods. In this research, we integrate the Human Error and Functional Failure Reasoning (HEFFR) framework into the fmdtools toolkit to enable designers to model the combined (machine, human, and joint) failures, including their propagation and dynamic effects, during early design stages. This integrated tool also allows designers to model the effects of performance shaping factors, team dynamics, and human-machine interactions in systems of systems. A demonstrative example of a remotely operated rover is explored to demonstrate how this approach can be applied to understand resilience in complex engineered systems with human interactions.
Lukman Irshad↗
Extreme Mapping: Looking for Water on the Moon
There are many challenges when exploring extreme environments. Gathering accurate data to build maps about places that you cannot go is incredibly complex. NASA supports scientists by remotely operating robotic rovers to explore uncharted territories. One potential upcoming mission is to look for water near a lunar pole (the Resource Prospector mission). Learn about the technical hurdles and research steps that NASA takes before the mission. NASA practices on Earth with Mission Analogs which simulate the proposed mission. This includes going to lunar-type landscapes, building field networks, testing out rovers, instruments and operational procedures. NASA sets up remote science back rooms just as there are for actual missions. NASA develops custom Ground Data Systems software to support scientific mission planning and monitoring over variable time delays, and separate commanding software and infrastructure to operate the rovers.
MOON↗
Results from Testing Crew-Controlled Surface Telerobotics on the International Space Station
During Summer 2013, the Intelligent Robotics Group at NASA Ames Research Center conducted a series of tests to examine how astronauts in the International Space Station (ISS) can remotely operate a planetary rover. The tests simulated portions of a proposed lunar mission, in which an astronaut in lunar orbit would remotely operate a planetary rover to deploy a radio telescope on the lunar far side. Over the course of Expedition 36, three ISS astronauts remotely operated the NASA "K10" planetary rover in an analogue lunar terrain located at the NASA Ames Research Center in California. The astronauts used a "Space Station Computer" (crew laptop), a combination of supervisory control (command sequencing) and manual control (discrete commanding), and Ku-band data communications to command and monitor K10 for 11 hours. In this paper, we present and analyze test results, summarize user feedback, and describe directions for future research.
robotics↗
Lunar Terrain Vehicle (LTV) Remote Teleoperation Studies Under Four Lunar Communication Latencies
Remotely operating a lunar rover from Earth while subject to an Earth-Moon time delay of multiple seconds could result in a dangerous state where the roving vehicle is either damaged or lost, thereby potentially compromising an entire mission or series of missions. Providing the right capabilities to the remote operator to manage inherent communication latencies will be important for remote driving to be successful. NASA conducted two studies to investigate the average speed and number of kilometers per day that an operator on Earth could teleoperate a notional Artemis unpressurized rover with minimal remote operator capabilities under 0- and 4-second communication delays (April 2023 study) and 6- and 8-second delays (August 2023 study). A primary goal of these studies was to understand if an Artemis Lunar Terrain Vehicle (LTV) could cover 6 kilometers (km) in 24 hours when operated remotely. During the April 2023 evaluation, eight test operators used an in-house simulation of the lunar surface South Pole to teleoperate a NASA government reference LTV. Each operator received approximately 30 minutes of remote driving familiarization/training prior to their test run. Operators viewed the surrounding terrain via a single, rover mast-mounted, high-resolution camera with pan/tilt/zoom capabilities; continuous communication was provided throughout all testing. In the August 2023 evaluation, remote operators received approximately 3 hours of familiarization training in each latency, and the simulation environment provided remote operators with an operator-selected rate limiter to enable finer sensitivity in the hand controller and a predictive circle function to better assist operators with predicting the path the vehicle could take. All test operators were able to successfully navigate and drive through six different types of terrain and five planned traverse scenarios using natural lighting under all communication delays. Results for average speeds for each communication delay, computed by averaging the data from all test conditions for that latency and all operators, are shown in the table below. The average speed data was then used to derive the total time needed to cover 6 km, 8 km, and 20 km (distances relevant to LTV-SYS071 and -029 requirements). Remote operators drove slower and used the brake more frequently when subject to a communication latency as opposed to no communication latency. Subjective workload assessments revealed that while operating in a latency the overall workload significantly increased when compared to a 0-s delay with mental demand, frustration, and performance being the primary contributing factors. Driving strategies in the 0-s delay did not vary significantly among subjects; however, in the 4-s delay condition, three different driving strategies were identified. In the 6-s and 8-s latency conditions the operator’s use of the cruise control to maintain speed was more apparent. Additionally, over the course of the August study, the operator took advantage of the predictive circle indicator on the navigation display and over 95% of the operator’s navigation used the mast camera 180-degree panning function for ground truthing in terms of boulders and craters. Operators started to define more specific parameters in driving strategies for general operations. This consisted of setting the vehicle into a low-speed cruise mode of approximately 11.5 kph and noticing driving performance of the vehicle seemed to be much harder at slower speeds 0.4–0.8 kph; however, the vehicle was more responsive at speeds of 2.9–3.6 kph. Regardless of communication delay, operators used both the horizontal translation rails and the vehicle fenders as guides to predict a path for the vehicle through heavily concentrated terrain features. Test operators acknowledged that the teleoperations training for this study was substantially less than what an actual LTV remote operator will ultimately receive. They estimated a minimum of 20 to 100 hours spread across multiple days and weeks (e.g., strategies included immersion training over a 3-day period, to a short 8-week starter program) would be needed to get an operator ~ 60% proficient (i.e., able to complete a subset of remote driving tasks), to a yearlong program for full proficiency in remote driving tasks under all terrain types and natural lighting conditions. Remotely operating a vehicle on another planetary body while subject to communication latency is a complex task. Speed, distance covered, time spent driving, time spent navigating, brake usage and rock contacts are all affected by operator workload, driving strategies, workstation ergonomics and training. These studies provided a “first-look” answer to a potential system requirement (namely if a remote operator could cover a given distance in a given amount of time); however, considerable general knowledge was gained to begin to understand what it will take to make a successful lunar rover teleoperator.
LTV↗
Lunar Terrain Vehicle (LTV) Remote Teleoperation Studies Under Four Lunar Communication Latencies
Remotely operating a lunar rover from Earth while subject to an Earth-Moon time delay of multiple seconds could result in a dangerous state where the roving vehicle is either damaged or lost, thereby potentially compromising an entire mission or series of missions. Providing the right capabilities to the remote operator to manage inherent communication latencies will be important for remote driving to be successful. The National Aeronautics and Space Administration (NASA) conducted two studies to investigate the average speed and number of kilometers per day that an operator on Earth could teleoperate a notional Artemis unpressurized rover with minimal remote operator capabilities under 0- and 4-second communication delays (April 2023 study) and 6- and 8-second delays (August 2023 study). A primary goal of these studies was to understand if an Artemis Lunar Terrain Vehicle (LTV) could cover 6 kilometers (km) in 24 hours when operated remotely. During the April 2023 evaluation, eight test operators used an in-house simulation of the lunar surface South Pole to teleoperate a NASA government reference LTV. Each operator received approximately 30 minutes of remote driving familiarization/training prior to their test run. Operators viewed the surrounding terrain via a single, rover mast-mounted, high-resolution camera with pan/tilt/zoom capabilities; continuous communication was provided throughout all testing. In the August 2023 evaluation, remote operators received approximately 3 hours of familiarization training in each latency, and the simulation environment provided remote operators with an operator-selected rate limiter to enable finer sensitivity in the hand controller and a predictive circle function to better assist operators with predicting the path the vehicle could take. All test operators were able to successfully navigate and drive through six different types of terrain and five planned traverse scenarios using natural lighting under all communication delays. Results for average speeds for each communication delay, computed by averaging the data from all test conditions for that latency and all operators, are shown in the table below. The average speed data was then used to derive the total time needed to cover 6 km, 8 km, and 20 km. Remote operators drove slower and used the brake more frequently when subject to a communication latency as opposed to no communication latency. Subjective workload assessments revealed that while operating in a latency the overall workload significantly increased when compared to a 0-s delay with mental demand, frustration, and performance being the primary contributing factors. Driving strategies in the 0-s delay did not vary significantly among subjects; however, in the 4-s delay condition, three different driving strategies were identified. In the 6-s and 8-s latency conditions the operator’s use of the cruise control to maintain speed was more apparent. Additionally, over the course of the August study, the operator took advantage of the predictive circle indicator on the navigation display and over 95% of the operator’s navigation used the mast camera 180-degree panning function for ground truthing in terms of boulders and craters. Operators started to define more specific parameters in driving strategies for general operations. This consisted of setting the vehicle into a low-speed cruise mode of approximately 1–1.5 kph and noticing driving performance of the vehicle seemed to be much harder at slower speeds 0.4–0.8 kph; however, the vehicle was more responsive at speeds of 2.9–3.6 kph. Regardless of communication delay, operators used both the horizontal translation rails and the vehicle fenders as guides to predict a path for the vehicle through heavily concentrated terrain features. Test operators acknowledged that the teleoperations training for this study was substantially less than what an actual LTV remote operator will ultimately receive. They estimated a minimum of 20 to 100 hours spread across multiple days and weeks (e.g., strategies included immersion training over a 3-day period, to a short 8-week starter program) would be needed to get an operator ~ 60% proficient (i.e., able to complete a subset of remote driving tasks), to a yearlong program for full proficiency in remote driving tasks under all terrain types and natural lighting conditions. Remotely operating a vehicle on another planetary body while subject to communication latency is a complex task. Speed, distance covered, time spent driving, time spent navigating, brake usage and rock contacts are all affected by operator workload, driving strategies, workstation ergonomics and training. These studies provided a “firstlook” answer to a potential system requirement (namely if a remote operator could cover a given distance in a given amount of time); however, considerable general knowledge was gained to begin to understand what it will take to make a successful lunar rover teleoperator.
LTV↗
A Multi-Decadal Sample Return Campaign Will Advance Lunar and Solar System Science and Exploration by 2050
There have been 11 missions to the Moon this century, 10 of which have been orbital, from 5 different space agencies. China became the third country to successfully soft-land on the Moon in 2013, and the second to successfully remotely operate a rover on the lunar surface. We now have significant global datasets that, coupled with the 1990s Clementine and Lunar Prospector missions, show that the sample collection is not representative of the lithologies present on the Moon. The M3 data from the Indian Chandrayaan-1 mission have identified lithologies that are not present/under-represented in the sample collection. LRO datasets show that volcanism could be as young as 100 Ma and that significant felsic complexes exist within the lunar crust. A multi-decadal sample return campaign is the next logical step in advancing our understanding of lunar origin and evolution and Solar System processes.
Neal, C. R.↗
Commanding Curiosity from the Couch: MSL Remote Operations, Challenges, and Path Ahead
This paper describes how the Mars ScienceLaboratory (MSL) project prepared for and successfully beganCuriosity rover Mars operations from their homes in responseto the COVID-19 work-from-home orders. In a very shortperiod, the team developed procedures and executed a remoteoperations readiness test in parallel with the team's support fornominal operations. Continuing regular rover operations withan entirely remote team had not previously been consideredfeasible due to a variety of factors. These included both thehuman factors, such as multiple concurrent person-to-personinteractions of the uplink planning team, as well as technicalfactors, such as reliance on powerful workstations dedicated tographically intensive software tools used for planning. The testwas conducted on March 12th, with both the downlink anduplink teams successfully simulating a near full planning day.The JPL administration announced the transition to mandatorytelework on Monday, March 16th. MSL stood down the uplinkplanning originally scheduled for the next day while downlinkcontinued monitoring the rover. Full operations then resumedper schedule with nearly the entire operations team teleworkingon Friday, March 20th, during which the team planned roveractivities for three Martian days (sols). These activities includedthe successful drilling of the "Edinburgh" rock target, a highlycomplex contact science activity.As of October 1st, 2020, the Mars Science Laboratory missionoperations team has conducted 88 remote tactical uplink shiftsfor a total of 190 sols of planned rover activity, which accountsfor more than 6% of the mission to date. In this period the roverhas completed four drilling campaigns and driven over 1150meters towards its next major science target – a sulfate bearinggeologic unit at the foot of Mount Sharp. Success has not beenwithout its challenges. Many of these have been addressed whileothers will remain in some form until the team can safely returnto JPL, which in turn is the largest challenge for the future.
Stroupe, Ashley↗
Application of the Core Flight System to a Lunar Rover
Resource Prospector (RP) is a lunar mission sponsored by NASAs Advanced Exploration Systems (AES) division, that aims to study in-situ resource utilization (ISRU) feasibility and technologies on the surface of the moon. The RP missions lunar surface segment includes a rover equipped with with a suite of instruments specifically designed to measure and map volatiles both at the surface and in the subsurface. Of particular interest is the quantity and state of volatiles in permanently shadowed regions. To conduct the mission, ground system operators will remotely drive the rover, directing it to waypoints along the surface in order to achieve measurement objectives. At selected locations, an onboard drill will be deployed to collect material and obtain direct measurements of the subsurface constituents. RP is currently planned for launch in 2022. RP is managed at NASA Ames Research Center. The RP Rover is being designed and developed by NASA Johnson Space Center (JSC) in partnership with NASA Ames. NASA Kennedy Space Center (KSC) is responsible for the Honeybee drilling system and science payload.In order to better understand the technical challenges and demonstrate capability, in 2015 the RP project developed a rover testbed (known as RP15). In this mission in a year, a rover was designed, developed, and outfitted with science instruments and a drill. The rover was operated from a remote operations center, and operated in an outdoor lunar rock yard at Johnson space center. The study was a resounding success meeting all objectives. The RP Rover software architecture and development processes were based on the successful Lunar Atmosphere and Dust Environment Explorer spacecraft. This architecture is built on the Core Flight System software and an interface to MatlabSimulink auto-generated software components known as the Simulink Interface Layer (SIL). The application of this lunar satellite inspired framework worked well for the rover application, and is currently being planned for the mission. This presentation provides an overview of the architecture and processes, and describes some of the changes and challenges for the rover application.
CFS↗
Application of CFS to a Lunar Rover: Resource Prospector (RP)
Resource Prospector (RP) is a lunar mission sponsored by NASA's Advanced Exploration Systems (AES) division, that aims to study in-situ resource utilization (ISRU) feasibility and technologies on the surface of the moon. The RP mission's lunar surface segment includes a rover equipped with with a suite of instruments specifically designed to measure and map volatiles both at the surface and in the subsurface. Of particular interest is the quantity and state of volatiles in permanently shadowed regions. To conduct the mission, ground system operators will remotely drive the rover, directing it to waypoints along the surface in order to achieve measurement objectives. At selected locations, an onboard drill will be deployed to collect material and obtain direct measurements of the subsurface constituents. RP is currently planned for launch in 2022. RP is managed at NASA Ames Research Center. The RP Rover is being designed and developed by NASA Johnson Space Center (JSC) in partnership with NASA Ames. NASA Kennedy Space Center (KSC) is responsible for the Honeybee drilling system and science payload. In order to better understand the technical challenges and demonstrate capability, in 2015 the RP project developed a rover testbed (known as RP15). In this mission in a year, a rover was designed, developed, and outfitted with science instruments and a drill. The rover was operated from a remote operations center, and operated in an outdoor lunar rock yard at Johnson space center. The study was a resounding success meeting all objectives. The RP Rover software architecture and development processes were based on the successful Lunar Atmosphere and Dust Environment Explorer spacecraft. This architecture is built on the Core Flight System software and an interface to Matlab/Simulink auto-generated software components known as the Simulink Interface Layer (SIL). The application of this lunar satellite inspired framework worked well for the rover application, and is currently being planned for the mission. This presentation provides an overview of the architecture and processes, and describes some of the changes and challenges for the rover application.
RP↗
Near Real Time Prospecting for Lunar Volatiles: Demonstrating RESOLVE Science in the Field
The Regolith and Environment Science and Oxygen & Lunar Volatile Extraction (RESOLVE) project aims to demonstrate the utility of "in situ resource utilization". In situ resource utilization (ISRU) is a way to rebalance the economics of spaceflight by reducing or eliminating materials that must be brought up from Earth and placed on the surface of the Moon for human use. RESOLVE is developing a rover-borne payload that (1) can locate near subsurface volatiles, (2) excavate and analyze samples of the volatile-bearing regolith, and (3) demonstrate the form, extractability and usefulness of the materials. Such investigations are important not only for ISRU but are also critically important for understanding the scientific nature of these intriguing lunar polar volatile deposits. Temperature models and orbital data suggest near surface volatile concentrations may exist at briefly lit lunar polar locations outside persistently shadowed regions. A lunar rover could be remotely operated at some of these locations for the 4-7 days of expected sunlight at relatively low cost. In July 2012 the RESOLVE project conducted a full-scale field demonstration. In particular, the ability to perform the real-time measurement analysis necessary to search for volatiles and the ability to combine the various measurement techniques to meet the mission measurement and science goals. With help from the Pacific International Space Center for Exploration Systems (PISCES), a lunar rover prototype (provided by the Canadian Space Agency) was equipped with prospecting instruments (neutron spectrometer and near-infrared spectrometer), subsurface access and sampling tools, including both an auger and coring drill (provided by CSA) and subsurface sample analysis instrumentation, including a sample oven system, the Oxygen and Volatile Extraction Node (OVEN), and Gas Chromatograph / Mass Spectrometer system, the Lunar Advanced Volatile Analysis (LAVA) system. Given the relatively short time period this lunar mission is being designed to, prospecting needs to occur in near real-time. The two prospecting instruments are the neutron and NIR spectrometers. In the field demo a small radioactive source was provided the neutron flux. The NIR spectrometer, which includes its own light source, looks at surface reflectance for signatures of bound H20/0H and general mineralogy. Once a "hot spot" was found by the prospecting instruments, the drill could either auger or core. The auger drill worked to a depth of 50 cm and is monitored with a drill camera and the NIR spectrometer. As cuttings are brought up the NIR spectra is monitored. If a particular location is considered of high -interest then the decision to core could be made. The coring drill (a push-tube) allowed a meter sample to be acquired processed by the OVEN/LAVA sys-tem. This presentation will provide details as how these instruments worked together and how and if the planned measurements and science was obtained.
Elphic, Richard↗
Manipulator control for rover planetary exploration
An anticipated goal of Mars surface exploration missions will be to survey and sample surface rock formations which appear scientifically interesting. In such a mission, a planetary rover would navigate close to a selected sampling site and the remote operator would use a manipulator mounted on the rover to perform a sampling operation. Techniques for accomplishing the necessary manipulation for the sampling components of such a mission have been developed and are presented. We discuss the implementation of a system for controlling a seven (7) degree of freedom Puma manipulator, equipped with a special rock gripper mounted on a planetary rover prototype, intended for the purpose of performing the sampling operation. Control is achieved by remote teleoperation. This paper discusses the real-time force control and supervisory control aspects of the rover manipulation system. Integration of the Puma manipulator with the existing distributed computer architecture is also discussed. The work described is a contribution toward achieving the coordinated manipulation and mobility necessary for a Mars sample acquisition and return scenario.
Cameron, Jonathan M.↗
Interviews with the Apollo lunar surface astronauts in support of planning for EVA systems design
Focused interviews were conducted with the Apollo astronauts who landed on the moon. The purpose of these interviews was to help define extravehicular activity (EVA) system requirements for future lunar and planetary missions. Information from the interviews was examined with particular attention to identifying areas of consensus, since some commonality of experience is necessary to aid in the design of advanced systems. Results are presented under the following categories: mission approach; mission structure; suits; portable life support systems; dust control; gloves; automation; information, displays, and controls; rovers and remotes; tools; operations; training; and general comments. Research recommendations are offered, along with supporting information.
Connors, Mary M.↗
Remote image analysis for Mars Exploration Rover mobility and manipulation operations
NASA's Mars Exploration Rovers are two sixwheeled, 175-kg robotic vehicles which have operated on Mars for over a year as of March 2005. The rovers are controlled by teams who must understand the rover's surroundings and develop command sequences on a daily basis. The tight tactical planning timeline and everchanging environment call for tools that allow quick assessment of potential manipulator targets and traverse goals, since command sequences must be developed in a matter of hours after receipt of new data from the rovers. Reachability maps give a visual indication of which targets are reachable by each rover's manipulator, while slope and solar energy maps show the rover operator which terrain areas are safe and unsafe from different standpoints.
image understanding↗
Mars rover local navigation and hazard avoidance
A Mars rover sample return mission has been proposed for the late 1990's. Due to the long speed-of-light delays between earth and Mars, some autonomy on the rover is highly desirable. JPL has been conducting research in two possible modes of rover operation, Computer-Aided Remote Driving and Semiautonomous Navigation. A recently-completed research program used a half-scale testbed vehicle to explore several of the concepts in semiautonomous navigation. A new, full-scale vehicle with all computational and power resources on-board will be used in the coming year to demonstrate relatively fast semiautonomous navigation. The computational and power requirements for Mars rover local navigation and hazard avoidance are discussed.
Wilcox, B. H.↗