2023-03-05 Meeting notes

 Date

Mar 5, 2023

 Participants

  • @Jinghao Lei

  • @Aaron Wang

  • @Christina Zhang

 Goals

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 Discussion topics

Item

Notes

Item

Notes

status check with Task 1

  • Is task 1 ready to go?

  • What are some integration is needed for task 1?

    • integration with the ground station about receiving QR code and call task1’s python file/function

Review of Task2 conop

  • The input will be a list of routes

  • Here is the output of given QR code

    • Route number 1: 2 pers; Lima; Quebec; 15 kg; obstacle 2 m to NE; $112
      Route number 2: 6 pers; Delta; Charlie; 5 kg; nil; $50
      Route number 3: 4 pers; Alpha; Zulu; 15 kg; other comment; $150

  • There will be a maximum of 50 routes

  • The Task 2 flight plan must start at Waypoint Alpha even if not part of a route.

  • There is no requirement to return to Alpha after completing the last route.

  • The landing sites will have only one pad

  • obstacles may be present as described in the QR code

  • obstacle 2m means: There will be obstacles near some pads no closer than 2m from the pad edge.

  • The algorithm must finish within 60 mins

  • The actual flight is limited to approximately 30-45 minutes

Current process / research?

NA

Metrics for evaluating the route

  • Price

  • weight limit

  • price/trip distance

  • starting point vs current location

  • distance from endpoint to base

  • Time is also a restriction

  • Note: We can ignore the number of person requirement because max # of passenger is 6 and we have a 6 person cabin → that means we can finish any route with one trip.

Ideas

  • Do preliminary searches based on the metrics and rule out the impossible routes (weights, very close obstacles.)

  • Pick a route starting from point Alpha (how to pick tbd)

  • sort reversely by value

  • ferry cost: cost from end point of this trip to the starting point of next trip (best case is 0 when ending point of this trip is the starting point of next trip)

  • battery swap cost: cost from end point of this trip to point Alpha (back to base)

  • trip cost: cost from start point to endpoint

  • Battery level: The current amount of battery

  • we decide which route to pick by considering: ferry cost, trip cost, trip value, battery swap cost

  • brute force is the way to go for now because there is only 50 routes and even less after preliminary searches.

Questions to ask other teams

  • How far is our estimated wing span? :2.4m

    • so it’s safe to say that we can deal with obstacles outside 3-5 m (needs more insight from the search experiment !!!)

  • battery life measurement: Is it ok that we use the distance as our cost for the trip? Is it possible to have a estimate (upper bound) of battery cost for example a 1.5 km trip with taking off and landing? ie is it possible to create a mapping between distance + takeoff + landing to battery percentage (10%) or equivalent? @Daniel Puratich @Ethan Abraham

  • Average speed of flight that we can reach to calculate for how many routes that we can finish.

 Action items

small task breakdowns

generate a list of test data (fake routes using random permutations of starting points and ending points, random values (uniform distribution from 1 to 200 dollars, and obstacle restrictions from 1 to 10 m from the edge of the landing pad. Num of person will be a uniform distribution from 1 to 6 but we don’t care about it)
Define flight plan output format and email-sending functionality
do more research on the algorithms itself

 Decisions