Perception-Aware Perching on Powerlines with Multirotors

This repo contains the code for the NLP-based perching trajectory generation presented in our paper "Perception-Aware Perching on Powerlines with Multirotors". It also contains the following example trajectories:

Upside down	90º	90º (Perception Aware)

Citing

If you use this code in an academic context, please cite the following publication:

@article{paneque2022perching,
  title={Perception-Aware Perching on Powerlines with Multirotors},
  author={Paneque, J. L., Martínez-de-Dios, J. R., Ollero, A., Hanover, D., Sun, S., Romero, A. and Scaramuzza, D.},
  journal={IEEE Robotics and Automation Letters},
  year={2022}
}

License

MIT License. Copyright (C) 2022 Julio L. Paneque, Jose Ramiro Martínez de Dios and Anibal Ollero (GRVC Robotics Lab, Universidad de Sevilla) and Drew Hanover, Sihao Sun, Ángel Romero and Davide Scaramuzza (Robotics and Perception Group, University of Zurich).

This is research code, expect that it changes often and any fitness for a particular purpose is disclaimed.

This work has dependencies on other libraries which are individually cited when appearing.

Requirements

The code was tested with Ubuntu 18.04, Matlab R2020b, FORCESPRO 5.1.0, Casadi 3.5.1, g++ 10.3.0 and libYAML-cpp 0.5. Compatibility with other versions should be possible but is not tested.

Installation and usage

Generating the solver (solver_generation)

The NLP solver is generated and run using the FORCESPRO software (https://forces.embotech.com/). A free academic license of the software can be requested in this link.

Once you have the license, install FORCESPRO following these instructions, and then install the MATLAB client following these instructions. After that, navigate to the solver_generation folder and run:

generate_solver.m

This will generate all the required files and copy them to the solver_interface folder.

Using the solver (solver_interface)

After the solver is generated, it can be used from the C++ interface to compute the required perching trajectories. To compile the interface, navigate to solver_interface and run:

g++ -o compute_perching_traj -Iinclude -std=c++17 src/perch_recovery_planner.cpp src/parameters/quad.cpp src/parameters/lines.cpp src/parameters/costs.cpp src/parameters/reference.cpp src/parameters/xinit.cpp extern/solver/PerchingSolver/lib/libPerchingSolver.so extern/solver/PerchingSolver_casadi2forces.c extern/solver/PerchingSolver_casadi.c -lm -lyaml-cpp

Once the code is compiled, it can be run given a path to a YAML file with the desired problem. This file provides the paths for the following sub-files (also in YAML format):

• The quadrotor parameters (quad_config)
• The powerlines setup (lines_config)
• The NLP costs for perching (perching_costs)
• The NLP costs for recovery (recovery_costs)
• The perching reference (reference)
• The starting position (xinit)

We provide the configuration files for three different perching maneuvers: upside_down, 90_deg_no_pa and 90_deg_pa. To run the first one, simply run:

./compute_perching_traj config/upside_down.yaml

This will compute the maneuver and generate an upside_down.csv file in the current directory. We already provide the resulting .csv files of the three maneuvers so they can be seen without compiling any code.

Visualizing the results (trajectory_visualization)

We provide a optional python script to visualize the generated maneuvers in 3D animated plots. The required packages to run it are listed in trajectory_visualization/requirements.txt. The script takes as inputs the trajectory file, the quadrotor configuration file and the powerlines setup file. Additional arguments --show_vel and --save can be used to show the quadrotor velocity overtime and to save the resulting animation as a gif file (note: saving the animation will take some time before anything is shown).

You can play an example animation by running:

python visualize_trajectory.py -t ../solver_interface/upside_down.csv -q ../solver_interface/config/quad_parameters.yaml -l ../solver_interface/config/upside_down/line_parameters.yaml --show_vel

This will show an animation of the upside_down perching maneuver.