2011 · 33 citations · 15 references
EngineeringAerospace EngineeringRobotics EngineeringField RoboticsRemote SensingRoboticsAutonomous ExplorationMission PlanningPlanetary ExplorationRobotics AutomationSpace ExplorationSubsurface ExplorationDeploymentExplorationExploration MissionsReconnaissanceReconnaissance AutomationReconnaissance TechniquesRobotic Space ExplorationSurface Exploration
Tier-scalable robotic reconnaissance missions are called for in extreme space environments, including planetary atmospheres, surfaces (both solid and liquid), and subsurfaces (e.g., oceans), as well as in potentially hazardous or inaccessible operational areas on Earth. Such future missions will require increasing degrees of operational autonomy: (1) Automatic mapping of an operational area from different vantages (i.e., spaceborne, airborne, surface, subsurface); (2) automatic sensor deployment and sensor data gathering; (3) automatic feature extraction and target/region-of-interest/anomaly identification within the mapped operational area; (4) automatic target prioritization for follow-up or close-up (in-situ) examination; and (5) subsequent automatic, targeted deployment and navigation/relocation of agents/sensors (e.g., to follow up on transient events). We report on recent progress in developing an Earth-based (outdoors) robotic test bed for Tier-scalable Reconnaissance at the University of Arizona and Caltech for distributed, science-driven, and significantly less constrained (compared to state-of-the-art) reconnaissance of prime locations on a variety of planetary bodies, with particular focus on Saturn's moon Titan with its methane/hydrocarbon lakes and Mars. The test bed currently comprises several computer-controlled robotic surface vehicles, i.e., rovers and lake landers/boats equipped with a variety of sensors. To achieve a fully operational Tier-scalable Reconnaissance test bed, aerial platforms will be integrated as a next step. The robotic surface vehicles can be interactively or automatically controlled from anywhere in the world in near real-time via the Internet. The test bed enables the implementation, field-testing, and validation of algorithms and strategies for navigation, exploration, sensor deployment, sensor data gathering, feature extraction, anomaly detection, and science goal prioritization for autonomous planetary exploration. Furthermore, it permits field-testing of novel instruments and sensor technologies, as well as testing of cooperative multi-agent scenarios and distributed scientific exploration of operational areas. As such the robotic test bed enables the development, implementation, field-testing, and validation of software packages for inter-agent communication and coordination to navigate and explore operational areas with greatly reduced reliance on (ultimately without assistance from) ground operators, thus affording the degree of mission autonomy/flexibility necessary to support future missions to Titan, Mars, and other planetary bodies, including asteroids.
15
Brian Hayes · Communications of the ACM · 2008 · 1.1K citations · Full text
Snapshot hyperspectral imaging in ophthalmology
William R. Johnson, Daniel W. Wilson, Wolfgang Fink et al. · Journal of Biomedical Optics · 2007 · 272 citations · Full text
Reagentless detection of microorganisms by intrinsic fluorescence
Cory Estes, Andrew Duncan, Christopher R. Lloyd et al. · Biosensors and Bioelectronics · 2003 · 69 citations
Tier-Scalable Reconnaissance Missions For The Autonomous Exploration Of Planetary Bodies
Wolfgang Fink, J. M. Dohm, Mark A. Tarbell et al. · 2007 · 45 citations