zhang-zengjie/CSUR-OptCov

Optimal coverage of multiple constant-speed unicycle robots

Optimal Coverage Control of Multiple Constant-Speed Unicycle Robots (CSUR)

• The experimental studies of a decentralized optimal coverage controller for multi-agent systems with multiple constant-speed unicycle robots (CSURs).
• This project is associated with the publication Distributed Coverage Control of Constrained Constant-Speed Unicycle Multi-Agent Systems.
• See a Youtube video how this project performs.

File Structure:

• sim_main.m: the main script to generate simulation results.
• exp_main.m: the main script to generate experimental results.
• /src: the source files.
• /lib: the library files.
• /data: the data files (go to this folder and download the data according to ReadMe.md, before running the code).

Requirements:

• Operating system: no specific requirements
• MATLAB: no specific requirements on versions

Quick Start

Generate figures of the simulation results

Run the sim_main.m script to generate figures for simulation.

Simulation study 1: different initial conditions

• Go to sim_main.m, change parameter setting script to set_sim_case_1_param, set_sim_case_1_param, or set_sim_case_1_param, for case 1, 2, or 3, respectively.
• Run

sim_main

Simulation study 2: different parameters

• Go to sim_main.m, change parameter setting script to set_sim_eps_10_param, set_sim_gamma_10_param, or set_sim_Q_10_param, for the influence of $\varepsilon$, $\gamma$, or $Q$, respectively.
• Run

sim_main

Simulation study 3: large number of robots

• Go to sim_main.m, change parameter setting script to set_sim_large_param.
• Run

sim_main

Simulation study 4: comparison with the conventional controller

• Go to sim_main.m, change parameter setting script to set_sim_proposed_param or set_sim_conv_param, for the proposed controller or the conventional controller, respectively.
• Run

sim_main

Generate figures of the experimental results

• Go to exp_main.m, change the case number to '1', '2', or'3', for case 1, 2, or 3, respectively.
• Run

exp_main