Contains two implemented algorithms to achieve multi-agent intermittent interaction planning. In the [IIP](./IIP) directory is the novel algorithm proposed in a recent RA-L submission (submission ID: 'tbd'). While in the [HS](./HS) directory is a method from [a related work][hollinger2010] ([later extended][hollinger2012]).
Contains two implemented algorithms to achieve multi-agent intermittent interaction planning. In the [IIP](./IIP) directory is the novel algorithm proposed in a recent RA-L submission (submission ID: `tbd`). While in the [HS](./HS) directory is a method from [a related work][hollinger2010] ([later extended][hollinger2012]).
## Table of Contents
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### Basic Usage
To run IIP with randomized initial conditions, run [multi_agent_path_planning.m](./IIP/multi_agent_path_planning.m) in MATLAB. Similarly for HS, run [main.m](.HS/main.m) in MATLAB. Depending on your directory structures you may need to edit 'main.m' to change the path. Also either method may return '-1' for all outputs if there is no feasible path for all agents, which can happen when obstacles are being randomly generated as in this case.
To run IIP with randomized initial conditions, run [multi_agent_path_planning.m](./IIP/multi_agent_path_planning.m) in MATLAB. Similarly for HS, run [main.m](.HS/main.m) in MATLAB. Depending on your directory structures you may need to edit `main.m` to change the path. Also either method may return `-1` for all outputs if there is no feasible path for all agents, which can happen when obstacles are being randomly generated as in this case.
### Monte Carlo Collection/Running
To run a monte carlo simulation comparing IIP with HS on the same set of scenarios, using all available cores in the processor, run [monteCarloParallel.m](./IIP/monteCarloParallel.m). If parallel execution is not required, [monteCarloRunner.m](./IIP/monteCarloRunner.m) can be run instead. To visualize the collected data, run [monteCarloPlotter.m](./IIP/monteCarloPlotter.m). You will have to update the 'filenames' list to include the newly collected data, which is automatically generated with a time stamped file name.
To run a monte carlo simulation comparing IIP with HS on the same set of scenarios, using all available cores in the processor, run [monteCarloParallel.m](./IIP/monteCarloParallel.m). If parallel execution is not required, [monteCarloRunner.m](./IIP/monteCarloRunner.m) can be run instead. To visualize the collected data, run [monteCarloPlotter.m](./IIP/monteCarloPlotter.m). You will have to update the `filenames` list to include the newly collected data, which is automatically generated with a time stamped file name.
