Install Obsidian on Ubuntu 20.04

Install Obsidian on Ubuntu 20.04

1. Go to https://obsidian.md/download and Download AppImage
2. Properties > Permission > Execute and check Allow execute this program
3. Go to https://en.wikipedia.org/wiki/File:2023_Obsidian_logo.svg and Download icon file of Obsidian
4. Generate desktop shortcuts for AppImage (this is much more convenient than clicking AppImage)

   sudo nano /usr/share/applications/obsidian.desktop

5. Copy and Paste below following lines and fix Name, Exec, Icon paths Ref

   [Desktop Entry]
   Name=YourApp
   Exec=/path/to/app.AppImage
   Icon=/path/to/nextcloud-icon.png
   comment=app
   Type=Application
   Terminal=false
   Encoding=UTF-8
   Categories=Utility;

6. Now you can use Obsidian shortcut with icon image on Ubuntu!

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paper

Paper Review: Model Predictive Contouring Control for Time-Optimal Quadrotor Flight

arxiv

Generating a time-optimal trajectory that considers the full quadrotor model requires solving a difficult time allocation problem which has high computational costs.

In this paper, the issue has overcomed by solving the time allocation problem and the control problem concurrently via MPCC.

The problem of the current state of the art

• Considering the full quadrotor dynamics including single-rotor thrust constraints requires solving a complex time allocation problem.
• The problem when the platform is at the limit of actuation is that the deviation happens from the preplanned trajectory.
  1. Conservative actuation which leads to speed sacrifice; the suboptimal path
  2. Online replanning; not possible with the current solver times.
• Efficient time-optimal waypoint planners can be divided into two types
  1. Modeling the platform as a point mass(PMM) → lacking the notion of 3D rotation and dynamically infeasible
  2. Approximating trajectories with polynomials. → smooth control inputs and the actuator potential are not fully exploited, rendering control policies suboptimal.

A Model Predictive Contouring Control(MPCC) in this paper balances the maximization of the progress along a given nominal path and the minimization of the distance to it.

The reference 3D path which does not need to be feasible, is generated by using a PMM method (so, PMM → 3D ref. path → MPCC → $u$).

[References] A review of contouring-error reduction method in multi-axis CNC machining Real-time contouring error estimation for multi-axis motion systems using the second-order approximation

(WIP)

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acados Installation

Installation

cd <path_to_install_acados>
git clone https://github.com/acados/acados.git
cd acados
git submodule update --recursive --init
 
mkdir -p build
cmake -B ./build -DACADOS_WITH_QPOASES=ON ..
# add more optional arguments e.g. -DACADOS_WITH_OSQP=OFF/ON -DACADOS_INSTALL_DIR=<path_to_acados_installation_folder> above
make install -j4

Done! :)

ACADO Toolkit Installation

Check out the differences between acados and ACADO Toolkit

• What is the difference between acados and ACADO?

• What is the difference between acados and ACADO?

Installation

sudo apt-get install gcc g++ cmake git gnuplot doxygen graphviz
git clone https://github.com/acado/acado.git -b stable ACADOtoolkit
cd ACADOtoolkit
mkdir build&& cd build
cmake .. && make -j4

Check the installation by running an example

cd ../examples/getting_started
./simple_ocp

Result! >> Covergence achieved. Demanded KKT tolerance is 1.000000e-06.