This hackathons is only open to students. Double check the event page for more information as this may mean only those from a particular university/country are eligible.
Event Type
online
44
Participants
3
Est. Projects
Organizers
Alex Johnson
alex@example.org
Jamie Rivera
jamie@example.org
Sam Chen
sam@example.org
Quality Score
Quality Score
72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
AeroHack is an advanced aerospace engineering challenge where teams build a single, unified mission planning + simulation framework that works for both aircraft and spacecraft. Your system must model real constraints, produce feasible mission plans, and demonstrate robustness through validation. Your solution must complete two linked tasks: 1) Aircraft Mission Task (UAV / Fixed-Wing) Plan and simulate a constrained flight mission that visits required waypoints while respecting: wind (time-varying and/or spatial), endurance / energy limits, turn-rate / bank-angle limits (or equivalent manoeuvre constraints), geofencing / no-fly polygons and altitude restrictions Objective: minimise mission time or energy while keeping constraint violations at zero and showing robustness under wind uncertainty (e.g., Monte-Carlo). 2) Spacecraft Mission Task (CubeSat-style LEO Ops) Generate a 7-day mission plan that schedules: target observations (Earth imaging / sensing opportunities), downlinks during ground-station contact windows (or computed passes) Subject to simplified spacecraft constraints such as: pointing / slew-rate limits (attitude feasibility), power/battery budget proxy, maximum operations per orbit / thermal-like duty cycle proxy Objective: maximise total “science value” delivered (targets successfully observed and downlinked) while avoiding constraint violations. Core requirement: Both tasks must use the same underlying planning concept (constraints + objective + solver/heuristic), not two unrelated scripts. The goal is to evaluate advanced skill in aerospace systems thinking, modelling, optimisation, and reproducible engineering.