Custom pathplanner that takes preferences into account

[thaije]

Custom pathplanner that takes preferences into account

[thaije]

See fa15b1e

[thaije]

Using the weighted pathplanner

• Add objects to your MATRX world with the traversability_penalty property, with a value > 0 and < 1, in addition to the is_traversable option (True or False). The agent will try to avoid objects with a high traversability_penalty (but will still walk over them if the path is much shorter).
• In the initialize function of your agent, initialize the navigator to use the new Navigator.WEIGHTED_A_STAR_ALGORITHM and with its settings like so:

# Initialize this agent's state tracker
self.state_tracker = StateTracker(agent_id=self.agent_id)

self.navigator = Navigator(agent_id=self.agent_id, action_set=self.action_set, algorithm=Navigator.WEIGHTED_A_STAR_ALGORITHM, algorithm_settings={"traversability_penalty_multiplier": 10})

For an example of an entire agent using the new pathplanner see this file: https://github.com/matrx-software/matrx/blob/319_custom_pathplanner(s)/matrx/agents/agent_types/patrolling_agent.py

Tweaking the weighted pathplanner

By increasing traversability_penalty_multiplier in the algorithm_settings above, the algorithm will try to avoid objects more aggresively with a traversability_penalty.

You can calculate this as follows:
For an agent that uses the pathplanner, normally 1 step sideways or upwards has a 'cost' of 1. However, if there is a object on route with a traversability_penalty=0.5 and the {traversability_penalty_multiplier": 10}, then walking over that object has a cost of 0.5*10=5, thus equal to walking over 5 normal tiles.

In this way, the agent will avoid to walk over this object. However, if the alternative is more than 5 normal tiles longer, it will opt t o walk over the slow tile instead.

Creating a custom pathplanner

It is also possible to create a new pathplanner, e.g. with a different pathplanner algorithm, or one that completely ignores the is_traversable such as maybe a drone would do. To do so:

• Change the navigator settings in your agent's initialize function as so:

self.navigator = Navigator(agent_id=self.agent_id, action_set=self.action_set,  algorithm="name_of_your_pathplanner",, custom_algorithm_class=YourCustomPathPlannerClass, traversability_map_func=your_custom_traversability_map_function, algorithm_settings={"settings_specific_to_your_pathplanner": True})

• Create the traversability_map_function that takes the current agent state, and converts it into a map of what is traversable and what not for your algorithm. See here for an example.
• Create a class for your pathplanner that takes the agent's action set (in what directions can it move) and settings for your algorithm. It should return a list of locations to traverse from the current location to the goal location. See here for an example.