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Repository associated with IROS 2021 submission " Embedded Hardware Appropriate Fast 3D Trajectory Optimization for Fixed Wing Aerial Vehicles by Levereging Hidden Convexities"

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Fixed-Wing-Aerial-TrajOpt

Repository associated with IROS 2021 submission " Embedded Hardware Appropriate Fast 3D Trajectory Optimization for Fixed Wing Aerial Vehicles by Levereging Hidden Convex structures"

Codes will start appearing here from Monday 14th March

Running our custom optimizer

  • Navigate to the ourOptimizer_50steps or ourOptimizer_100steps folder and edit configuration details in config.yaml file.
  • In config.yaml file, entering psi_init as 0.2 indicates 0.2pi in main code.
  • Run the following command g++ main.cpp FWV_optim.cpp $(pkg-config --cflags --libs yaml-cpp) -o test -O2 followed by ./test
  • To visualize, run gnuplot graph.plt
    How to change steps (Edit global variable num in main.cpp file)

Running generated ACADO code

  • Navigate to any of the config folder and run make clean all followed by ./test.
    Note: Only for the first time do make clean all otherwise just make

Configuration taken for Comparison

Config No. x y z psi (*pi) xg yg zg planning time steps
1 5 130 30 0 120 40 10 13.8 50
2 5 130 30 0 120 40 10 13.8 100
3 5 130 30 -0.2 120 40 10 13.8 50
4 5 130 30 -0.2 120 40 10 13.7 100
5 -30 -10 30 0.2 130 138 40 18.3 50
6 -30 -10 30 0.2 130 138 40 18.3 100
7 -30 -10 30 0 130 138 40 19.3 50
8 -30 -10 30 0 130 138 40 19.3 100
9 -30 -10 30 0.33 130 138 40 18.4 50
10 -30 -10 30 0.33 130 138 40 18.3 100
11 -30 -10 30 0.5 130 138 40 18.6 50
12 -30 -10 30 0.5 130 138 40 18.6 100
13 -30 -10 30 -0.2 130 138 40 19.5 50
14 -30 -10 30 -0.2 130 138 40 19.5 100
15 5 130 30 0.2 120 40 10 13.9 50
16 5 130 30 0.2 120 40 10 14 100
17 5 130 30 -0.33 120 40 10 12.9 50
18 5 130 30 -0.33 120 40 10 12.9 100
19 5 130 30 -0.45 120 40 10 13.4 50
20 5 130 30 -0.45 120 40 10 13.4 100

For each planning time and steps acado code was generated.

Generating ACADO code

  • Install ACADO Toolkit
  • Copy getting_started.cpp from acadoOptim folder and paste it to /ACADOtoolkit/examples/code_generation/mpc_mhe.
  • Edit getting_started.cpp for desired settings (steps, planning time).
  • Navigate to ACADOtoolkit/build and run make code_generation_getting_started.
  • Finally run ./code_generation_getting_started in folder /ACADOtoolkit/examples/code_generation/mpc_mhe.

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Repository associated with IROS 2021 submission " Embedded Hardware Appropriate Fast 3D Trajectory Optimization for Fixed Wing Aerial Vehicles by Levereging Hidden Convexities"

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