AI Seminar
Energy-Aware Flight Planning for Unattended Unmanned Seaplane Operation
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The Flying Fish autonomous unmanned seaplane is designed and built for persistent
ocean surveillance. Solar energy harvesting and always-on autonomous control
and guidance are required to achieve unattended long-term operation. This presentation
will describe the energy-aware flight planning and guidance/navigation/control algorithms required for
Flying Fish to execute drift-flight cycles that fly over or drift through regions of interest while maintaining
a watch circle of operation despite winds and limited energy availability.
autonomously execute drift-ight cycles necessary to maintain. Seaplane kinematics
and dynamics are summarized, followed by our successful efforts to fully-automate
watch circle crossing drift-flight cycles. A graph-based mission planner combines models of global solar energy, local ocean-currents, and wind to provide an energy-aware flight planning tool. An NP-hard asymmetric multi-visit traveling salesman planning problem is posed that integrates vehicle performance and environment models using energy as the primary cost metric. A novel A* search heuristic is
presented to improve search efficiency relative to uniform cost search. A series of cases
studies are conducted with surface and airborne goals for various times of day and
for multi-day scenarios. Energy-optimal solutions are identified except in cases where
energy harvesting produces multiple comparable-cost plans via negative-cost cycles.