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Modify documentation for get_path according to the guidelines
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@@ -38,28 +38,31 @@ The function returns a sequence of actions that can be applied to the agent to t | |
- [if path found] array of agent actions that can guide the agent from its start state to its goal region | ||
- [if path not found] empty array | ||
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### 2) get_path | ||
returns the path followed by the agent from a given starting state under a given dynamics function and given sequence of actions. | ||
### 2) `get_path` | ||
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get_path(start_state, action_sequence, dynamics) | ||
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The function returns the path followed by the agent from a given starting state under a given dynamics function and given sequence of actions. | ||
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Function parameters: | ||
* *start_state* -> specifies the agent's starting state. | ||
* *action_sequence* -> array of agent actions to be applied in sequence | ||
* dynamics -> function describing the dynamics of the agent. It takes in the state and an action as inputs and outputs the next resulting state. | ||
* ```next_state = dynamics(state,action)``` | ||
#### Arguments | ||
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- `start_state::Any`: specifies the agent's starting state. | ||
- `action_sequence::AbstractVector`: array of agent actions to be applied in sequence | ||
- `dynamics::Function`: function describing the dynamics of the agent. It takes in the state and an action as inputs and outputs the next resulting state. | ||
It will be called like this: `next_state = dynamics(state,action)` | ||
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#### Output | ||
- array of agent states from its start state to the final state after applying all the actions in the action_sequence | ||
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Output: | ||
* array of agent states from its start state to the final state after applying all the actions in the action_sequence | ||
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Usage: | ||
*** | ||
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``` | ||
agent_path = get_path(start_state, action_sequence, dynamics) | ||
``` | ||
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#### Examples | ||
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#### A simple example to find path for a holonomic vehicle using the Hybrid A* algorithm can be found in examples/demo_holonomic_vehicle.jl | ||
1) A simple example to find path for a holonomic vehicle using the Hybrid A* algorithm can be found in examples/demo_holonomic_vehicle.jl | ||
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#### A more complex example of finding a drivable path for a Dubin's car using the Hybrid A* algorithm can be found in examples/demo_dubin_car.jl | ||
2) A more complex example of finding a drivable path for a Dubin's car using the Hybrid A* algorithm can be found in examples/demo_dubin_car.jl | ||
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In case of any queries, feel free to raise a Github Issue or reach out to the author via email at [email protected]. | ||
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