Human Supervision of Robotic Site Surveys

Mathematics – Logic

Scientific paper

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Lunar, Planetary, And Deep-Space Probes, Neural Networks, Fuzzy Logic, Artificial Intelligence, Computer Interfaces, Servo And Control Equipment, Robots

Scientific paper

Ground operators will interact remotely with robots on the lunar surface to support site preparation and survey. Astronauts will interact with robots to support outpost buildup and maintenance, as well as mission operations. One mode of interaction required for such operations is the ability to supervise robots performing routine autonomous tasks. Supervision of autonomous robotic activities requires monitoring the robot's performance of tasks with minimal human effort. This includes understanding its progress on tasks, awareness when important milestones are achieved or problems impede tasks, and reconstructing situations after the fact by relating task events to recorded data. We are developing a software framework to support such interaction among distributed human teams and robots. We are evaluating our framework for human supervision of mobile robots performing routine site survey operations. We are prototyping a system that (1) monitors data from the K10 robot performing surveys to determine the depth of permafrost at the Haughton Crater on Devon Island, (2) computes performance measures about how well the survey is going, (3) builds summaries of these performance measures, and (4) notifies to appropriate personnel when milestones are achieved or performance indicates a problem. We will evaluate our prototype using data collected during Operational Readiness Tests for the Haughton Crater field test to be conducted in July 2007. In this paper we describe our approach for human supervision of robotic activities and report the results of our evaluation with the K10 robot.

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