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NASA NTRS2013

Helicopter Field Testing of NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) System fully Integrated with the Morpheus Vertical Test Bed Avionics

The Autonomous Landing and Hazard Avoidance Technology (ALHAT) Project was chartered to develop and mature to a Technology Readiness Level (TRL) of six an autonomous system combining guidance, navigation and control with real-time terrain sensing and recognition functions for crewed, cargo, and robotic planetary landing vehicles. The ALHAT System must be capable of identifying and avoiding surface hazards to enable a safe and accurate landing to within tens of meters of designated and certified landing sites anywhere on a planetary surface under any lighting conditions. This is accomplished with the core sensing functions of the ALHAT system: Terrain Relative Navigation (TRN), Hazard Detection and Avoidance (HDA), and Hazard Relative Navigation (HRN). The NASA plan for the ALHAT technology is to perform the TRL6 closed loop demonstration on the Morpheus Vertical Test Bed (VTB). The first Morpheus vehicle was lost in August of 2012 during free-flight testing at Kennedy Space Center (KSC), so the decision was made to perform a helicopter test of the integrated ALHAT System with the Morpheus avionics over the ALHAT planetary hazard field at KSC. The KSC helicopter tests included flight profiles approximating planetary approaches, with the entire ALHAT system interfaced with all appropriate Morpheus subsystems and operated in real-time. During these helicopter flights, the ALHAT system imaged the simulated lunar terrain constructed in FY2012 to support ALHAT/Morpheus testing at KSC. To the best of our knowledge, this represents the highest fidelity testing of a system of this kind to date. During this helicopter testing, two new Morpheus landers were under construction at the Johnson Space Center to support the objective of an integrated ALHAT/Morpheus free-flight demonstration. This paper provides an overview of this helicopter flight test activity, including results and lessons learned, and also provides an overview of recent integrated testing of ALHAT on the second Morpheus vehicle.

Epp, Chirold D.↗
NASA NTRS1994

Integration for navigation on the UMASS mobile perception lab

Integration of real-time visual procedures for use on the Mobile Perception Lab (MPL) was presented. The MPL is an autonomous vehicle designed for testing visually guided behavior. Two critical areas of focus in the system design were data storage/exchange and process control. The Intermediate Symbolic Representation (ISR3) supported data storage and exchange, and the MPL script monitor provided process control. Resource allocation, inter-process communication, and real-time control are difficult problems which must be solved in order to construct strong autonomous systems.

Draper, Bruce↗
NASA NTRS2000

Navigation Strategy for the Mars 2001 Lander Mission

The Mars Surveyor Program (MSP) is an ongoing series of missions designed to robotically study, map and search for signs of life on the planet Mars. The MSP 2001 project will advance the effort by sending an orbiter, a lander and a rover to the red planet in the 2001 opportunity. Each vehicle will carry a science payload that will Investigate the Martian environment on both a global and on a local scale. Although this mission will not directly search for signs of life, or cache samples to be returned to Earth, it will demonstrate certain enabling technologies that will be utilized by the future Mars Sample Return missions. One technology that is needed for the Sample Return mission is the capability to place a vehicle on the surface within several kilometers of the targeted landing site. The MSP'01 Lander will take the first major step towards this type of precision landing at Mars. Significant reduction of the landed footprint will be achieved through two technology advances. The first, and most dramatic, is hypersonic aeromaneuvering; the second is improved approach navigation. As a result, the guided entry will produce in a footprint that is only tens of kilometers, which is an order of magnitude improvement over the Pathfinder and Mars Polar Lander ballistic entries. This reduction will significantly enhance scientific return by enabling the potential selection of otherwise unreachable landing sites with unique geologic interest and public appeal. A landed footprint reduction from hundreds to tens of kilometers is also a milestone on the path towards human exploration of Mars, where the desire is to place multiple vehicles within several hundred meters of the planned landing site. Hypersonic aeromaneuvering is an extension of the atmospheric flight goals of the previous landed missions, Pathfinder and Mars Polar Lander (MPL), that utilizes aerodynamic lift and an autonomous guidance algorithm while in the upper atmosphere. The onboard guidance algorithm will control the direction of the lift vector, via bank angle modulation, to keep the vehicle on the desired trajectory. While numerous autonomous guidance algorithms have been developed for use during hypersonic flight at Earth, this will be the first flight of an autonomously directed lifting entry vehicle at Mars. However, without sufficient control and knowledge of the atmospheric entry conditions, the guidance algorithm will not perform effectively. The goal of the interplanetary navigation strategy is to deliver the spacecraft to the desired entry condition with sufficient accuracy and knowledge to enable satisfactory guidance algorithm performance. Specifically, the entry flight path angle must not exceed 0.27 deg. to a 3 sigma confidence level. Entry errors will contribute directly to the size of the landed footprint and the most significant component is entry flight path angle. The size of the entry corridor is limited on the shallow side by integrated heating constraints, and on the steep side by deceleration (g-load) and terminal descent propellant. In order to meet this tight constraint it is necessary to place a targeting maneuver seven hours prior to the time of entry. At this time the trajectory knowledge will be quite accurate, and the effects of maneuver execution errors will be small. The drawback is that entry accuracy is dependent on the success of this final late maneuver. Because propulsive maneuvers are critical events, it is desirable to minimize their occurrence and provide the flight team with as much response time as possible in the event of a spacecraft fault. A mission critical maneuver at Entry - 7 hours does not provide much fault tolerance, and it is desirable to provide a strategy that minimizes reliance on this maneuver. This paper will focus on the Improvements in interplanetary navigation that will decrease entry errors and will reduce the landed footprint, even in the absence of aeromaneuvering. The easiest to take advantage of are Improvements In the knowledge of the Mars ephemeris and gravity field due to the MGS and MSP'98 missions. Improvements In data collection and reduction techniques such as "precislon ranging' and near-simultaneous tracking will also be utilized. In addition to precise trajectory control, a robust strategy for communications and flight operations must also be demonstrated. The result Is a navigation and communications strategy on approach that utilizes optimal maneuver placement to take advantage of trajectory knowledge, minimizes risk for the flight operations team, is responsive to spacecraft hardware limitations, and achieves the entry corridor. The MSP2001 mission Is managed at JPL under the auspices of the Mars Exploration Directorate. The spacecraft flight elements are built and managed by Lockheed-Martin Astronautics in Denver, Colorado.

Mase, Robert A.↗
NASA NTRS2011

Onboard Atmospheric Modeling and Prediction for Autonomous Aerobraking Missions

Aerobraking has proven to be an effective means of increasing the science payload for planetary orbiting missions and/or for enabling the use of less expensive launch vehicles. Though aerobraking has numerous benefits, large operations cost have been required to maintain the aerobraking time line without violating aerodynamic heating or other constraints. Two operations functions have been performed on an orbit by orbit basis to estimate atmospheric properties relevant to aerobraking. The Navigation team typically solves for an atmospheric density scale factor using DSN tracking data and the atmospheric modeling team uses telemetric accelerometer data to recover atmospheric density profiles. After some effort, decisions are made about the need for orbit trim maneuvers to adjust periapsis altitude to stay within the aerobraking corridor. Autonomous aerobraking would reduce the need for many ground based tasks. To be successful, atmospheric modeling must be performed on the vehicle in near real time. This paper discusses the issues associated with estimating the planetary atmosphere onboard and evaluates a number of the options for Mars, Venus and Titan aerobraking missions.

Tolson, Robert H.↗
NASA NTRS2015

Advanced Bayesian Method for Planetary Surface Navigation

Autonomous Exploration, Inc., has developed an advanced Bayesian statistical inference method that leverages current computing technology to produce a highly accurate surface navigation system. The method combines dense stereo vision and high-speed optical flow to implement visual odometry (VO) to track faster rover movements. The Bayesian VO technique improves performance by using all image information rather than corner features only. The method determines what can be learned from each image pixel and weighs the information accordingly. This capability improves performance in shadowed areas that yield only low-contrast images. The error characteristics of the visual processing are complementary to those of a low-cost inertial measurement unit (IMU), so the combination of the two capabilities provides highly accurate navigation. The method increases NASA mission productivity by enabling faster rover speed and accuracy. On Earth, the technology will permit operation of robots and autonomous vehicles in areas where the Global Positioning System (GPS) is degraded or unavailable.

Center, Julian↗
NASA NTRS2019

Safe2Ditch Steer-To-Clear Development and Flight Testing

This paper describes a series of small unmanned aerial system (sUAS) flights performed at NASA Langley Research Center in April and May of 2019 to test a newly added Steer-to-Clear feature for the Safe2Ditch (S2D) prototype system. S2D is an autonomous crash management system for sUAS. Its function is to detect the onset of an emergency for an autonomous vehicle, and to enable that vehicle in distress to execute safe landings to avoid injuring people on the ground or damaging property. Flight tests were conducted at the City Environment Range for Testing Autonomous Integrated Navigation (CERTAIN) range at NASA Langley. Prior testing of S2D focused on rerouting to an alternate ditch site when an occupant was detected in the primary ditch site. For Steer-to-Clear testing, S2D was limited to a single ditch site option to force engagement of the Steer-to-Clear mode. The implementation of Steer-to-Clear for the flight prototype used a simple method to divide the target ditch site into four quadrants. An RC car was driven in circles in one quadrant to simulate an occupant in that ditch site. A simple implementation of Steer-to- Clear was programmed to land in the opposite quadrant to maximize distance to the occupant’s quadrant. A successful mission was tallied when this occurred. Out of nineteen flights, thirteen resulted in successful missions. Data logs from the flight vehicle and the RC car indicated that unsuccessful missions were due to geolocation error between the actual location of the RC car and the derived location of it by the Vision Assisted Landing component of S2D on the flight vehicle. Video data indicated that while the Vision Assisted Landing component reliably identified the location of the ditch site occupant in the image frame, the conversion of the occupant’s location to earth coordinates was sometimes adversely impacted by errors in sensor data needed to perform the transformation. Logged sensor data was analyzed to attempt to identify the primary error sources and their impact on the geolocation accuracy. Three trends were observed in the data evaluation phase. In one trend, errors in geolocation were relatively large at the flight vehicle’s cruise altitude, but reduced as the vehicle descended. This was the expected behavior and was attributed to sensor errors of the inertial measurement unit (IMU). The second trend showed distinct sinusoidal error for the entire descent that did not always reduce with altitude. The third trend showed high scatter in the data, which did not correlate well with altitude. Possible sources of observed error and compensation techniques are discussed.

Petty, Bryan J.↗
NASA NTRS2015

Automated Point Cloud Correspondence Detection for Underwater Mapping Using AUVs

An algorithm for automating correspondence detection between point clouds composed of multibeam sonar data is presented. This allows accurate initialization for point cloud alignment techniques even in cases where accurate inertial navigation is not available, such as iceberg profiling or vehicles with low-grade inertial navigation systems. Techniques from computer vision literature are used to extract, label, and match keypoints between "pseudo-images" generated from these point clouds. Image matches are refined using RANSAC and information about the vehicle trajectory. The resulting correspondences can be used to initialize an iterative closest point (ICP) registration algorithm to estimate accumulated navigation error and aid in the creation of accurate, self-consistent maps. The results presented use multibeam sonar data obtained from multiple overlapping passes of an underwater canyon in Monterey Bay, California. Using strict matching criteria, the method detects 23 between-swath correspondence events in a set of 155 pseudo-images with zero false positives. Using less conservative matching criteria doubles the number of matches but introduces several false positive matches as well. Heuristics based on known vehicle trajectory information are used to eliminate these.

Sonar↗
NASA NTRS2014

High-Fidelity Flash Lidar Model Development

NASA's Autonomous Landing and Hazard Avoidance Technologies (ALHAT) project is currently developing the critical technologies to safely and precisely navigate and land crew, cargo and robotic spacecraft vehicles on and around planetary bodies. One key element of this project is a high-fidelity Flash Lidar sensor that can generate three-dimensional (3-D) images of the planetary surface. These images are processed with hazard detection and avoidance and hazard relative navigation algorithms, and then are subsequently used by the Guidance, Navigation and Control subsystem to generate an optimal navigation solution. A complex, high-fidelity model of the Flash Lidar was developed in order to evaluate the performance of the sensor and its interaction with the interfacing ALHAT components on vehicles with different configurations and under different flight trajectories. The model contains a parameterized, general approach to Flash Lidar detection and reflects physical attributes such as range and electronic noise sources, and laser pulse temporal and spatial profiles. It also provides the realistic interaction of the laser pulse with terrain features that include varying albedo, boulders, craters slopes and shadows. This paper gives a description of the Flash Lidar model and presents results from the Lidar operating under different scenarios.

Hines, Glenn D.↗
NASA NTRS2009

NASA #837 Tribute The Jet with a Thousand Faces

This slide presentation reviews the TF-1 (later designated as an F-15B) aircraft, which was delivered as an F-15 trainer. The aircraft was used as a test aircraft for various programs. The aircraft was later renamed to NASA 837 in 2001. Prior to its retirement it was used to test various features and concepts. Some of these tests were: (1) Canopy Off Testing, (2) STOL and Maneuvering Technology Demonstrator (S/MTD), (3) 2D Nozzles (4) Autonomous landing guidance, (5) Advanced Control Technology for Integrated Vehicles (ACTIVE), (6) Intelligent Flight Control System (IFCS), (7) Structural Loads Model Validation (SLMV), (8) Enhanced Communication and Navigation System (ECANS), (9) QuietSpike Probing, and (10) Lift and Nozzle Effects on Tail Shocks (LaNCETS)

Rhoades, Carrie M.↗
NASA NTRS2010

360-Degree Visual Detection and Target Tracking on an Autonomous Surface Vehicle

This paper describes perception and planning systems of an autonomous sea surface vehicle (ASV) whose goal is to detect and track other vessels at medium to long ranges and execute responses to determine whether the vessel is adversarial. The Jet Propulsion Laboratory (JPL) has developed a tightly integrated system called CARACaS (Control Architecture for Robotic Agent Command and Sensing) that blends the sensing, planning, and behavior autonomy necessary for such missions. Two patrol scenarios are addressed here: one in which the ASV patrols a large harbor region and checks for vessels near a fixed asset on each pass and one in which the ASV circles a fixed asset and intercepts approaching vessels. This paper focuses on the ASV's central perception and situation awareness system, dubbed Surface Autonomous Visual Analysis and Tracking (SAVAnT), which receives images from an omnidirectional camera head, identifies objects of interest in these images, and probabilistically tracks the objects' presence over time, even as they may exist outside of the vehicle's sensor range. The integrated CARACaS/SAVAnT system has been implemented on U.S. Navy experimental ASVs and tested in on-water field demonstrations.

ASV (AUTONOMOUS SEA SURFACE VEHICLE)↗
NASA NTRS2024

Looking to the Future: A Call to Action for Advanced GNC Algorithm Verification and Validation

Future space systems will rely on autonomous Guidance, Navigation, and Control (GNC) functions to efficiently manage safe and precise self-directed operations in uncertain complex environments. Fundamentally, the GNC system plays a key role in mission performance and safety because it computes the ideal trajectory (Guidance), determines the actual trajectory (Navigation), and executes the ideal trajectory (Control) of a vehicle’s position and attitude. Our current GNC systems are highly automated and already have a high degree of complexity. As missions become more ambitious, GNC systems for launch vehicles and space platforms (e.g., spacecraft, probes, and landers) will require higher levels of performance and autonomous operation than previously encountered, for example, this includes GNC for optimizing aerodynamic and/or propulsion performance during planetary entry. This GNC Verification and Validation (V&V) paper highlights concerns with what undoubtedly will be a trend towards increased complexity as fully autonomous GNC systems are developed for future space missions. Clearly, complex GNC systems pose challenges in the prelaunch V&V phase, which is a relatively expensive part of a mission’s life cycle. Essentially the V&V phase is focused on checking that the system effectively meets all the design and operational requirements for the mission. The authors of this paper (i.e., the Inter-Agency Working Group of GNC subject matter experts) focused on this fundamental question over the past few years: Will the GNC engineering community of practice be sufficiently prepared to perform the necessary V&V on evolving GNC architectures that are driven by very demanding requirements for autonomy, resiliency, reconfigurability, adaptability, and mission cost-benefit balance? It is the viewpoint of our Inter-Agency team that the GNC V&V approaches and processes needed to address the next generation of complex GNC systems, which likely will employ various forms of modern GNC technology, are not currently established to the level the community will need in the future. While researchers and practitioners have made some progress in developing new GNC V&V methods for modern GNC systems, a good deal of work remains to be done to codify such methods in a comprehensive and systematic manner. Thus, the Inter-Agency team’s partner organizations [the National Aeronautics and Space Administration (NASA), the European Space Agency (ESA), the National Centre for Space Studies (CNES), the German Aerospace Center (DLR), the French Aerospace Lab (ONERA), and ISAE-SUPAERO] have conducted preliminary investigations into advancing GNC V&V techniques, which resulted in the identification of the need for education, new V&V tools, and benchmark problems for the GNC community. The necessary proactive steps to be taken to meet the challenges and fill the gaps in GNC V&V are summarized in this paper. The first steps include identifying advanced analysis tools, developing a GNC V&V roadmap, and expanding education and training programs for GNC practitioners. This paper is a call to action and proposes a comprehensive set of recommended actions for all our stakeholders: space agencies, researchers, and industry.

Samir Bennani↗
NASA NTRS2000

Autonomous Relative Navigation for Formation-Flying Satellites Using GPS

The Goddard Space Flight Center is currently developing advanced spacecraft systems to provide autonomous navigation and control of formation flyers. This paper discusses autonomous relative navigation performance for a formation of four eccentric, medium-altitude Earth-orbiting satellites using Global Positioning System (GPS) Standard Positioning Service (SPS) and "GPS-like " intersatellite measurements. The performance of several candidate relative navigation approaches is evaluated. These analyses indicate that an autonomous relative navigation position accuracy of 1meter root-mean-square can be achieved by differencing high-accuracy filtered solutions if only measurements from common GPS space vehicles are used in the independently estimated solutions.

Gramling, Cheryl↗
NASA NTRS2000

The Deep Space 4/Champollion Comet Rendezvous and Lander Technology Demonstration Mission

The Deep Space 4/Champollion mission is designed to test and validate technologies for landing on and anchoring to small bodies, and sample collection and transfer, in preparation for future sample return missions from comets, asteroids, and satellites. in addition, DS-4 will test technologies for advanced, multi-engine solar electric propulsion (SEP) systems, inflatable-rigidizable solar arrays, autonomous navigation and precision guidance for landing, autonomous hazard detection and avoidance, and advanced integrated avionics and packaging concepts. Deep Space-4/Champollion consists of two spacecraft: an orbiter/carrier vehicle which includes the multi-engine SEP stage, and a lander, called Champollion, which will descend to the surface of the 46P/Tempel 1 cometary nucleus. The spacecraft will launch in April, 2003 and land on the comet in September, 2006 Deep Space 4/Champollion is a joint project between NASA and CNES, the French space agency.

Smythe, William D.↗
NASA NTRS2009

Flight Test Performance of a High Precision Navigation Doppler Lidar

A navigation Doppler Lidar (DL) was developed at NASA Langley Research Center (LaRC) for high precision velocity measurements from a lunar or planetary landing vehicle in support of the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project. A unique feature of this DL is that it has the capability to provide a precision velocity vector which can be easily separated into horizontal and vertical velocity components and high accuracy line of sight (LOS) range measurements. This dual mode of operation can provide useful information, such as vehicle orientation relative to the direction of travel, and vehicle attitude relative to the sensor footprint on the ground. System performance was evaluated in a series of helicopter flight tests over the California desert. This paper provides a description of the DL system and presents results obtained from these flight tests.

Pierrottet, Diego↗
NASA NTRS2016

Approach-Phase Precision Landing with Hazard Relative Navigation: Terrestrial Test Campaign Results of the Morpheus/ALHAT Project

The Morpheus Project began in late 2009 as an ambitious e ort code-named Project M to integrate three ongoing multi-center NASA technology developments: humanoid robotics, liquid oxygen/liquid methane (LOX/LCH4) propulsion and Autonomous Precision Landing and Hazard Avoidance Technology (ALHAT) into a single engineering demonstration mission to be own to the Moon by 2013. The humanoid robot e ort was redirected to a deploy- ment of Robonaut 2 on the International Space Station in February of 2011 while Morpheus continued as a terrestrial eld test project integrating the existing ALHAT Project's tech- nologies into a sub-orbital ight system using the world's rst LOX/LCH4 main propulsion and reaction control system fed from the same blowdown tanks. A series of 33 tethered tests with the Morpheus 1.0 vehicle and Morpheus 1.5 vehicle were conducted from April 2011 - December 2013 before successful, sustained free ights with the primary Vertical Testbed (VTB) navigation con guration began with Free Flight 3 on December 10, 2013. Over the course of the following 12 free ights and 3 tethered ights, components of the ALHAT navigation system were integrated into the Morpheus vehicle, operations, and ight control loop. The ALHAT navigation system was integrated and run concurrently with the VTB navigation system as a reference and fail-safe option in ight (see touchdown position esti- mate comparisons in Fig. 1). Flight testing completed with Free Flight 15 on December 15, 2014 with a completely autonomous Hazard Detection and Avoidance (HDA), integration of surface relative and Hazard Relative Navigation (HRN) measurements into the onboard dual-state inertial estimator Kalman lter software, and landing within 2 meters of the VTB GPS-based navigation solution at the safe landing site target. This paper describes the Mor- pheus joint VTB/ALHAT navigation architecture, the sensors utilized during the terrestrial ight campaign, issues resolved during testing, and the navigation results from the ight tests.

Crain, Timothy P.↗
NASA NTRS2011

Autonomous Landing and Ingress of Micro-Air-Vehicles in Urban Environments Based on Monocular Vision

Unmanned micro air vehicles (MAVs) will play an important role in future reconnaissance and search and rescue applications. In order to conduct persistent surveillance and to conserve energy, MAVs need the ability to land, and they need the ability to enter (ingress) buildings and other structures to conduct reconnaissance. To be safe and practical under a wide range of environmental conditions, landing and ingress maneuvers must be autonomous, using real-time, onboard sensor feedback. To address these key behaviors, we present a novel method for vision-based autonomous MAV landing and ingress using a single camera for two urban scenarios: landing on an elevated surface, representative of a rooftop, and ingress through a rectangular opening, representative of a door or window. Real-world scenarios will not include special navigation markers, so we rely on tracking arbitrary scene features; however, we do currently exploit planarity of the scene. Our vision system uses a planar homography decomposition to detect navigation targets and to produce approach waypoints as inputs to the vehicle control algorithm. Scene perception, planning, and control run onboard in real-time; at present we obtain aircraft position knowledge from an external motion capture system, but we expect to replace this in the near future with a fully self-contained, onboard, vision-aided state estimation algorithm. We demonstrate autonomous vision-based landing and ingress target detection with two different quadrotor MAV platforms. To our knowledge, this is the first demonstration of onboard, vision-based autonomous landing and ingress algorithms that do not use special purpose scene markers to identify the destination.

micro air vehicles (MAVs)↗
NASA NTRSDate not supplied

Architecture Options for Navigation in Cislunar Space for Human Landing System Vehicles

As part of architecture studies and insight analysis focused on requirements development into Human Landing System lunar architecture designs, multiple studies are underway to understand the sensitivities and options for achieving high precision landing on the lunar surface. The baseline approach utilizes a combination of multiple sensors to capture autonomous state observations of the lander with respect to the lunar surface. These systems are typically constrained in terms of operational altitudes by parameters such as onboard map size, camera focus, or sensor transmitted power (for altimeter observations). While these sensor suites do enable high precision landing, they are typically very complex and expensive. For a human-rated vehicle, fault detection algorithms are needed in addition to redundant sensors drive additional design complexity. Conversely, for these early missions, mass performance is key, so extended analysis is required to identify numbers of sensors, their ideal placement, and integration algorithms. A key part of this analysis is to help identify key sensor suites and options to help alleviate this design tension. An alternate approach is to take advantage and build out in-situ assets to allow for GPS-like navigation within the lunar regime through the use of navigation references or beacons. This can be achieved through the integration of navigation services into potential relays and pre-placed lunar surface assets. This research focuses on the capability of this infrastructure to support navigation in all areas of cislunar space such as: approach to the moon, in orbit around the moon, and ascent/descent operations to the surface. An augmented state linear covariance analysis (LinCov) and navigation state covariance analysis (NavCov) tools were used to assess a variety of navigation reference locations and how they can support vehicle operations through both understanding of state uncertainties and trajectory dispersions. This research helps to supplement existing studies focused on communication link analysis by providing additional insight into specific vehicle operational scenarios that are tied closely to potential Human Landing System scenarios. Key aspect of this analysis focus on the sensitivity to state knowledge of the references, the accuracy of inter-asset measurements, and placement in support of the various scenarios.

Evan J Anzalone↗
NASA NTRS2007

Rover Graphical Simulator

Rover Graphical Simulator (RGS) is a package of software that generates images of the motion of a wheeled robotic exploratory vehicle (rover) across terrain that includes obstacles and regions of varying traversability. The simulated rover moves autonomously, utilizing reasoning and decision-making capabilities of a fuzzy-logic navigation strategy to choose its path from an initial to a final state. RGS provides a graphical user interface for control and monitoring of simulations. The numerically simulated motion is represented as discrete steps with a constant time interval between updates. At each simulation step, a dot is placed at the old rover position and a graphical symbol representing the rover is redrawn at the new, updated position. The effect is to leave a trail of dots depicting the path traversed by the rover, the distances between dots being proportional to the local speed. Obstacles and regions of low traversability are depicted as filled circles, with buffer zones around them indicated by enclosing circles. The simulated robot is equipped with onboard sensors that can detect regional terrain traversability and local obstacles out to specified ranges. RGS won the NASA Group Achievement Award in 2002.

Bon, Bruce↗