Abstract-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.
The paper presents two systems called PATS and SAP that when integrated realize Sensor Web Enablement (SWE) of spatially distributed mobile sensors. The Personal Alert and Tracking System (PATS) consists of a networked collection of customdesigned low-power wireless nodes, arranged in ad-hoc network topologies, to provide tracking for wild land firefighters. These mobile nodes form arbitrary network topologies and use a multihop packet routing protocol to relay sensor data to the command center. The multi-hop capability enables robust communication in a variety of environments by routing around natural and manmade terrain features. Situational Awareness and Prediction (SAP) works with the PATS sensor network to convert sensor data to information and to provide real-time collaborative situational awareness. The goal is to deliver a resource utilizing intelligent reasoning coupled with rule-based actionable intelligence using diverse knowledge fusion and modal trend forecasting. The SAP makes this data available to information sharing middleware using OGC standards.The paper describes the architecture of both the PATS and SAP systems and how these two systems interoperate with each other. The SAP system works in concert with the Unified Incident Command and Decision Support (UICDS) information sharing middleware to provide data fusion from multiple sources. UICDS can then publish the sensor data using the OGC's Web Mapping Service, Web Feature Service, and Sensor Observation Service standards. The system described in the paper is able to integrate a spatially distributed sensor system, operating without the benefit of the Web infrastructure, with a remote monitoring and control system that is equipped to take advantage of SWE.
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