Pyroboplan

https://pyroboplan.readthedocs.io/en/latest/
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Pyroboplan is an educational Python library for manipulator motion planning, extensively using...
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### pyroboplan.models.two_dof.load_models

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.models.html

Gets the example 2-DOF models.

```APIDOC
## pyroboplan.models.two_dof.load_models

### Description
Gets the example 2-DOF models.

### Returns
A 3-tuple containing the model, collision geometry model, and visual geometry model.

### Return type
tuple[pinocchio.Model]
```

--------------------------------

### pyroboplan.models.marble.load_models

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.models.html

Gets the example 2-DOF models for the marble.

```APIDOC
## pyroboplan.models.marble.load_models

### Description
Gets the example 2-DOF models resembling a marble labyrinth.

### Returns
A 3-tuple containing the model, collision geometry model, and visual geometry model.

### Return type
tuple[pinocchio.Model]
```

--------------------------------

### pyroboplan.models.panda.load_models

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.models.html

Gets the example Panda models.

```APIDOC
## pyroboplan.models.panda.load_models

### Description
Gets the example Panda models.

### Returns
A 3-tuple containing the model, collision geometry model, and visual geometry model.

### Return type
tuple[pinocchio.Model]
```

--------------------------------

### pyroboplan.models.ur10.load_ur10_on_base_models

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.models.html

Gets the example UR10 on base models.

```APIDOC
## pyroboplan.models.ur10.load_ur10_on_base_models

### Description
Gets the example UR10 on base models.

### Returns
A 3-tuple containing the model, collision geometry model, and visual geometry model.

### Return type
tuple[pinocchio.Model]
```

--------------------------------

### get_example_models_folder

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.models.html

Returns the absolute path to the directory containing the example models for pyroboplan.

```APIDOC
## get_example_models_folder

### Description
Returns the full path the example models folder.

### Returns
The path to the pyroboplan example models folder.

### Return Type
str
```

--------------------------------

### pyroboplan.models.utils

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Utility functions for accessing example model paths.

```APIDOC
## pyroboplan.models.utils

### Description
Utility functions for model-related operations.

### Functions
- `get_example_models_folder()`: Returns the path to the example models folder.
```

--------------------------------

### load_ur5_on_base_models

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.models.html

Retrieves the example UR5 on base models, returning the robot model, its collision geometry model, and its visual geometry model.

```APIDOC
## load_ur5_on_base_models

### Description
Gets the example UR5 on base models.

### Returns
A 3-tuple containing the model, collision geometry model, and visual geometry model.

### Return Type
tuple[pinocchio.Model]
```

--------------------------------

### astar

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.planning.html

Finds the shortest path between the start_pose and goal_pose using the A* algorithm. Both the start and goal poses must be present in the Graph.

```APIDOC
## astar

### Description
Finds the shortest path between the start_pose and goal_pose using the A* algorithm. Both the start and goal poses must be present in the Graph.

### Parameters
#### Path Parameters
- **graph** (pyroboplan.planning.graph.Graph) – The graph containing the nodes and edges.
- **start_pose** (pyroboplan.planning.graph.Node) – The starting robot configuration.
- **goal_pose** (pyroboplan.planning.graph.Node) – The goal robot configuration.
- **heuristic** (function(pyroboplan.planning.graph.Node, pyroboplan.planning.graph.Node)) – Heuristic function for estimating the distance between two nodes. For A* this will be used to compute the configuration space distance between a visited node (arg1) and the goal node (arg2). Defaults to `pyroboplan.core.utils.configuration_distance()`.

### Returns
- **path** (list of pyroboplan.planning.graph.Node) – The sequence of nodes representing a path from start_node to goal_node.
```

--------------------------------

### dfs

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.planning.html

Find a path between the start_pose and goal_pose using a depth first search (DFS). Both the start and goal poses must be present in the Graph.

```APIDOC
## dfs

### Description
Find a path between the start_pose and goal_pose using a depth first search (DFS). Both the start and goal poses must be present in the Graph.

### Parameters
#### Path Parameters
- **graph** (pyroboplan.planning.graph.Graph) – The graph containing the nodes and edges.
- **start_pose** (pyroboplan.planning.graph.Node) – The starting robot configuration.
- **goal_pose** (pyroboplan.planning.graph.Node) – The goal robot configuration.

### Returns
- **path** (list of pyroboplan.planning.graph.Node) – The sequence of nodes representing a path from start_node to goal_node.
```

--------------------------------

### retrace_path

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.planning.html

Retraces a path from a goal node back to the root node (a node without a parent). The path is returned in order from the start to the goal.

```APIDOC
## retrace_path

### Description
Retraces a path to the specified goal_node from a root node (a node with no parent). The resulting path will be returned in order form the start at index 0 to the goal_node at the index -1.

### Parameters
#### Path Parameters
* **goal_node** (pyroboplan.planning.graph.Node) - Required - The starting joint configuration.

### Returns
A list a nodes from the root to the specified goal_node.

### Return Type
list[pyroboplan.planning.graph.Node]
```

--------------------------------

### RRTPlanner

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.planning.html

Rapidly-expanding Random Tree (RRT) planner. This is a sampling-based motion planner that finds collision-free paths from a start to a goal configuration.

```APIDOC
## RRTPlanner

### Description
Rapidly-expanding Random Tree (RRT) planner. This is a sampling-based motion planner that finds collision-free paths from a start to a goal configuration.

### Parameters
* **_model_** - The robot model.
* **_collision_model_** - The collision model.
* **_options** (pyroboplan.planning.rrt.RRTPlannerOptions, optional) - Options for the RRT planner. Defaults to RRTPlannerOptions().

### Methods
#### add_node_to_tree(_tree_, _q_new_, _parent_node_)
Add a new node to the tree. If the RRT* algorithm is enabled, will also rewire.

Parameters:
* **tree** (pyroboplan.planning.graph.Graph) – The tree to which to add the new node.
* **q_new** (_array-like_) – The robot configuration from which to create a new tree node.
* **parent_node** (pyroboplan.planning.graph.Node) – The parent node to connect the new node to.

Returns:
The new node that was added to the tree.

Return type:
pyroboplan.planning.graph.Node

#### extend_or_connect(_tree_, _parent_node_, _q_sample_)
Extends a tree towards a sampled node with steps no larger than the maximum connection distance.

Parameters:
* **tree** (pyroboplan.planning.graph.Graph) – The tree to use when performing this operation.
* **parent_node** (pyroboplan.planning.graph.Node) – The node from which to start extending or connecting towards the sample.
* **q_sample** (_array-like_) – The robot configuration sample to extend or connect towards.

Returns:
The latest node that was added to the tree, or None if no node was found.

Return type:
pyroboplan.planning.graph.Node, optional

#### extract_path_from_trees(_start_tree_final_node_, _goal_tree_final_node_=None)
Extracts the final path from the RRT trees from the start tree root to the goal tree root passing through both final nodes.

Parameters:
* **start_tree_final_node** (pyroboplan.planning.graph.Node) – The last node of the start tree.
* **goal_tree_final_node** (pyroboplan.planning.graph.Node, optional) – The last node of the goal tree. If None, this means the goal tree is ignored.

Returns:
A list of robot configurations describing the path waypoints in order.

Return type:
list[array-like]

#### plan(_q_start_, _q_goal_)
Plans a path from a start to a goal configuration.

Parameters:
* **q_start** (_array-like_) – The starting robot configuration.
* **q_goal** (_array-like_) – The goal robot configuration.

#### reset()
Resets all the planning data structures.

#### visualize(_visualizer_=None, _frame_name_, _path_name_='planned_path', _tree_name='rrt', _show_path=True, _show_tree=False_)
Visualizes the RRT path.

Parameters:
* **visualizer** (pinocchio.visualize.meshcat_visualizer.MeshcatVisualizer, optional) – The visualizer to use for this solver.
* **frame_name** (_str_) – The name of the frame to use when visualizing paths in Cartesian space.
* **path_name** (_str_, optional) – The name of the MeshCat component for the path.
* **tree_name** (_str_, optional) – The name of the MeshCat component for the tree.
* **show_path** (_bool_, optional) – If true, shows the final path from start to goal.
* **show_tree** (_bool_, optional) – If true, shows the entire sampled tree.
```

--------------------------------

### CubicTrajectoryOptimization.plan

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.trajectory.html

Plans a trajectory from a start to a goal configuration, or along an entire trajectory. It can automatically determine intermediate waypoints or use a provided initial guess for path waypoints.

```APIDOC
## plan

### Description
Plans a trajectory from a start to a goal configuration, or along an entire trajectory. If the input list has 2 elements, then this is assumed to be the start and goal configurations. The intermediate waypoints will be determined automatically. If the input list has more than 2 elements, then these are the actual waypoints that must be achieved.

### Method
plan

### Parameters
#### Path Parameters
- **q_path** (list[array-like]) - Required - A list of joint configurations describing the desired motion.
- **init_path** (list[array-like], optional) - Optional - If set, defines the initial guess for the path waypoints.

### Returns
- Optional[pyroboplan.trajectory.polynomial.CubicPolynomialTrajectory] - The resulting trajectory, or None if optimization failed
```

--------------------------------

### get_normalized_path_scaling

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.planning.html

Calculates and returns a list of length-normalized scaling values for each waypoint along a given path. These values range from 0.0 at the start to 1.0 at the end.

```APIDOC
## get_normalized_path_scaling

### Description
Returns a list of length-normalized scaling values along a joint configuration path, from 0.0 at the start to 1.0 at the end.

### Parameters
* **q_path** (list[array-like]) – The list of joint configurations describing the path.

### Returns
The list of scaling values, between 0.0 and 1.0, at each of the path waypoints.

### Return type
list[float]
```

--------------------------------

### get_minimum_distance_at_state

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.core.html

Gets the minimum distance to collision at a specified state.

```APIDOC
## get_minimum_distance_at_state

### Description
Gets the minimum distance to collision at a specified state.

### Parameters
* **model** (pinocchio.Model) – The model to use for collision checking.
* **collision_model** (pinocchio.Model) – The collision model to use for collision checking.
* **q** (array-like) – The joint configuration of the model.
* **data** (pinocchio.Data, optional) – The model data to use for collision checking. If None, data is created automatically.
* **collision_data** (pinocchio.GeometryData, optional) – The collision_model data to use for collision checking. If None, data is created automatically.

### Returns
The minimum distance to collision, in meters.

### Return type
float
```

--------------------------------

### PRMPlannerOptions Class

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.planning.html

Options for Probabilistic Roadmap (PRM) planning, including parameters like maximum step size, neighbor radius, and maximum nodes.

```APIDOC
## PRMPlannerOptions

### Description
Options for Probabilistic Roadmap (PRM) planning.

### Parameters
- **max_step_size** (float, optional) - Defaults to 0.05.
- **max_neighbor_radius** (float, optional) - Defaults to 0.5.
- **max_neighbor_connections** (int, optional) - Defaults to 15.
- **max_construction_nodes** (int, optional) - Defaults to 5000.
- **construction_timeout** (float, optional) - Defaults to 10.0.
- **rng_seed** (None, optional) - Defaults to None.
- **prm_star** (bool, optional) - Defaults to False.
- **prm_file** (None, optional) - Defaults to None.
```

--------------------------------

### PRMPlanner Class

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.planning.html

The PRMPlanner class implements a sampling-based motion planner that constructs a graph in the free configuration space and searches for a path. Graphs can be persisted to disk.

```APIDOC
## PRMPlanner

### Description
Probabilistic Roadmap (PRM) planner. This is a sampling-based motion planner that constructs a graph in the free configuration space and then searches for a path using standard graph search functions. Graphs can be persisted to disk for use in future applications.

### Methods

#### `connect_node(new_node, radius, k)`
Identifies all neighbors and makes connections to the added node.

Parameters:
- **new_node** (pyroboplan.planning.graph.Node) – The node to add.
- **radius** (float) – Only consider connections within the provided radius.
- **k** (int) – Only consider up to a maximum of k neighbors to make connections.

Returns:
True if the node was connected to the graph. False otherwise.

Return type:
bool

#### `connect_planning_nodes(start_node, goal_node)`
Ensures the start and goal configurations can be connected to the PRM.

Parameters:
- **start_node** (pyroboplan.planning.graph.Node) – The start node to connect.
- **goal_node** (pyroboplan.planning.graph.Node) – The goal node to connect.

Returns:
True if the nodes were able to be connected, False otherwise.

Return type:
bool

#### `construct_roadmap(sample_generator=None)`
Grows the graph by sampling nodes using the provided generator, then connecting them to the Graph. The caller can optionally override the default generator, if desired.

Parameters:
- **sample_generator** (Generator | None) – The sample function to use in construction of the roadmap. Defaults to randomly sampling the robot’s configuration space.

#### `plan(q_start, q_goal)`
Plans a path from a start to a goal configuration using the constructed graph.

Parameters:
- **q_start** (array-like) – The starting robot configuration.
- **q_goal** (array-like) – The goal robot configuration.

Returns:
A path from the start to the goal state, if one exists. Otherwise None.

Return type:
list[array-like]

#### `reset()`
Resets the PRM’s transient data between queries.

#### `visualize(visualizer, frame_name, path_name='planned_path', graph_name='prm', show_path=True, show_graph=False)`
Visualizes the PRM and the latest path found within it.

Parameters:
- **visualizer** (pinocchio.visualize.meshcat_visualizer.MeshcatVisualizer | None) – The visualizer to use for this solver.
- **frame_name** (str) – The name of the frame to use when visualizing paths in Cartesian space.
- **path_name** (str, optional) – The name of the MeshCat component for the path.
- **graph_name** (str, optional) – The name of the MeshCat component for the tree.
- **show_path** (bool, optional) – If true, shows the final path from start to goal.
- **show_graph** (bool, optional) – If true, shows the entire PRM graph.
```

--------------------------------

### get_collision_geometry_ids

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.core.html

Gets a list of collision geometry model IDs for a specified body name.

```APIDOC
## get_collision_geometry_ids

### Description
Gets a list of collision geometry model IDs for a specified body name.

### Parameters
* **model** (pinocchio.Model) – The model to use for getting frame IDs.
* **collision_model** (pinocchio.Model) – The model to use for collision checking.
* **body** (str) – The name of the body. This can be directly the name of a geometry in the collision model, or it can be the name of the frame in the main model.

### Returns
A list of collision geometry IDs corresponding to the body name.

### Return type
list[int]
```

--------------------------------

### pyroboplan.planning.path_shortcutting

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Provides functions for shortcutting and normalizing paths to improve efficiency and reduce path length.

```APIDOC
## pyroboplan.planning.path_shortcutting

### Description
Functions for shortcutting and normalizing paths.

### Functions
- `get_configuration_from_normalized_path_scaling()`
- `get_normalized_path_scaling()`
- `shortcut_path()`
```

--------------------------------

### RRTPlannerOptions

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.planning.html

Options for Rapidly-exploring Random Tree (RRT) planning.

```APIDOC
## RRTPlannerOptions

### Description
Options for Rapidly-exploring Random Tree (RRT) planning.

### Parameters
* **_max_step_size** (float, optional) - Defaults to 0.05.
* **_max_connection_dist** (float, optional) - Defaults to inf.
* **_rrt_connect** (bool, optional) - Defaults to False.
* **_bidirectional_rrt** (bool, optional) - Defaults to False.
* **_rrt_star** (bool, optional) - Defaults to False.
* **_max_rewire_dist** (float, optional) - Defaults to inf.
* **_max_planning_time** (float, optional) - Defaults to 10.0.
* **_rng_seed** (int, optional) - Defaults to None.
* **_fast_return** (bool, optional) - Defaults to True.
* **_goal_biasing_probability** (float, optional) - Defaults to 0.0.
* **_collision_distance_padding** (float, optional) - Defaults to 0.0.
```

--------------------------------

### pyroboplan.planning.utils

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Utility functions for path discretization, extension, and collision checking within the planning module.

```APIDOC
## pyroboplan.planning.utils

### Description
Utility functions for planning operations.

### Functions
- `discretize_joint_space_path()`
- `discretized_joint_space_generator()`
- `extend_robot_state()`
- `has_collision_free_path()`
- `retrace_path()`
```

--------------------------------

### pyroboplan.core.utils

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Provides utility functions for collision checking, state manipulation, and path analysis within the PyRoboPlan core.

```APIDOC
## pyroboplan.core.utils

### Description
Utility functions for collision checking, state manipulation, and path analysis.

### Functions
- `calculate_collision_vector_and_jacobians()`
- `check_collisions_along_path()`
- `check_collisions_at_state()`
- `check_within_limits()`
- `configuration_distance()`
- `extract_cartesian_pose()`
- `extract_cartesian_poses()`
- `get_collision_geometry_ids()`
- `get_collision_pair_indices_from_bodies()`
- `get_minimum_distance_at_state()`
- `get_path_length()`
- `get_random_collision_free_state()`
- `get_random_collision_free_transform()`
- `get_random_state()`
- `get_random_transform()`
- `set_collisions()`
```

--------------------------------

### Build Robot Models from URDF

Source: https://pyroboplan.readthedocs.io/en/latest/_sources/motion_planning.rst.txt

Imports robot models, collision models, and visual models from a URDF file using Pinocchio.

```python
import pinocchio

filename = "/path/to/your.urdf"
model, collision_model, visual_model = pinocchio.buildModelsFromUrdf(filename)
```

--------------------------------

### pyroboplan.planning.graph_search

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Implements graph search algorithms such as A* and Depth-First Search (DFS) for pathfinding within planning graphs.

```APIDOC
## pyroboplan.planning.graph_search

### Description
Graph search algorithms for pathfinding.

### Functions
- `astar()`: Performs A* search on a graph.
- `dfs()`: Performs Depth-First Search on a graph.
```

--------------------------------

### load_from_file

Source: https://pyroboplan.readthedocs.io/en/latest/genindex.html

Loads a graph from a file. This is a class method of the pyroboplan.planning.graph.Graph class.

```APIDOC
## load_from_file()

### Description
Loads a graph from a file.

### Class
pyroboplan.planning.graph.Graph

### Method
Class Method
```

--------------------------------

### visualize_path

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.visualization.html

Visualizes a single path of poses as lines using MeshCat, showing only the translation component.

```APIDOC
## visualize_path

### Description
Visualizes a path of poses as lines containing only the translation component.

### Parameters
- **visualizer** (pinocchio.visualize.meshcat_visualizer.MeshcatVisualizer) – The visualizer instance.
- **name** (str) – The name of the MeshCat component to add.
- **tforms** (list[pinocchio.SE3]) – A list of transforms representing the vertices of the path.
- **line_width** (float, optional) – The width of the axes in the triad. Defaults to 3.
- **line_color** (array-like, optional) – The line color to use. Defaults to [0.0, 0.0, 0.0].
```

--------------------------------

### visualize_paths

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.visualization.html

Visualizes a list of paths of poses as lines using MeshCat, showing only the translation component.

```APIDOC
## visualize_paths

### Description
Visualizes a list of paths of poses as lines containing only the translation component.

### Parameters
- **visualizer** (pinocchio.visualize.meshcat_visualizer.MeshcatVisualizer) – The visualizer instance.
- **name** (str) – The name of the MeshCat component to add.
- **paths** (list[list[pinocchio.SE3]]) – A list of paths, each of which is a list of transforms representing the vertices of the path.
- **line_width** (float, optional) – The width of the axes in the triad. Defaults to 3.
- **line_color** (array-like, optional) – The line color to use. Defaults to [0.0, 0.0, 0.0].
```

--------------------------------

### pyroboplan.planning.rrt

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Implements the Rapidly-exploring Random Tree (RRT) planner for efficient motion planning.

```APIDOC
## pyroboplan.planning.rrt

### Description
Rapidly-exploring Random Tree (RRT) planner.

### Classes
- `RRTPlanner`
  - `RRTPlanner.add_node_to_tree()`: Adds a node to the RRT.
  - `RRTPlanner.extend_or_connect()`: Extends or connects nodes in the RRT.
  - `RRTPlanner.extract_path_from_trees()`: Extracts a path from the RRT.
  - `RRTPlanner.plan()`: Plans a path using the RRT planner.
  - `RRTPlanner.reset()`: Resets the RRT planner.
  - `RRTPlanner.visualize()`: Visualizes the RRT.
- `RRTPlannerOptions`: Options for configuring the RRT planner.
```

--------------------------------

### Compute Forward Kinematics and Jacobian

Source: https://pyroboplan.readthedocs.io/en/latest/_sources/motion_planning.rst.txt

Calculates the forward kinematics and Jacobian for a specified frame and joint configuration using Pinocchio.

```python
data = model.createData()
target_frame_id = model.getFrameId("my_frame")

# Forward kinematics
pinocchio.framesForwardKinematics(model, data, q_target)
my_frame_transform = data.oMf[target_frame_id]

# Jacobian
jac = pinocchio.computeFrameJacobian(
    model, data, q, target_frame_id, pinocchio.ReferenceFrame.LOCAL,
)
```

--------------------------------

### shortcut_path

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.planning.html

Applies path shortcutting to shorten a given path by iteratively connecting random points along the path, ensuring collision-free connections. This aims to find a shorter, valid path.

```APIDOC
## shortcut_path

### Description
Performs path shortcutting by sampling two random points along the path and verifying whether those two points can be connected directly without collisions. This implementation is based on section 3.5.3 of: https://motion.cs.illinois.edu/RoboticSystems/MotionPlanningHigherDimensions.html

### Parameters
* **model** (pinocchio.Model) – The model of the robot.
* **collision_model** (pinocchio.Model.) – The model to use for collision checking.
* **q_path** (list[array-like]) – The list of joint configurations describing the path.
* **max_iters** (int) – The maximum iterations for randomly sampling shortcut points. Defaults to 100.
* **max_step_size** (float) – Maximum joint configuration step size for collision checking along path segments. Defaults to 0.05.

### Returns
The shortest length path over all the shortcutting attempts.

### Return type
list[array-like]
```

--------------------------------

### load_models

Source: https://pyroboplan.readthedocs.io/en/latest/genindex.html

Loads models for various robot configurations. Supported modules include marble, panda, and two_dof.

```APIDOC
## load_models()

### Description
Loads models for various robot configurations.

### Supported Modules
- pyroboplan.models.marble
- pyroboplan.models.panda
- pyroboplan.models.two_dof
```

--------------------------------

### pyroboplan.planning.prm

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Implements the Probabilistic Roadmap (PRM) planner for motion planning in high-dimensional spaces.

```APIDOC
## pyroboplan.planning.prm

### Description
Probabilistic Roadmap (PRM) planner.

### Classes
- `PRMPlanner`
  - `PRMPlanner.connect_node()`: Connects a node to the roadmap.
  - `PRMPlanner.connect_planning_nodes()`: Connects planning nodes to the roadmap.
  - `PRMPlanner.construct_roadmap()`: Constructs the PRM roadmap.
  - `PRMPlanner.plan()`: Plans a path using the PRM planner.
  - `PRMPlanner.reset()`: Resets the PRM planner.
  - `PRMPlanner.visualize()`: Visualizes the PRM roadmap.
- `PRMPlannerOptions`: Options for configuring the PRM planner.
- `random_model_state_generator()`: Generates random states for the model.
```

--------------------------------

### pyroboplan.ik.nullspace_components

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Provides functions to compute nullspace components for inverse kinematics, aiding in tasks like collision avoidance and joint limit adherence.

```APIDOC
## pyroboplan.ik.nullspace_components

### Description
Functions to compute nullspace components for inverse kinematics.

### Functions
- `collision_avoidance_nullspace_component()`
- `joint_center_nullspace_component()`
- `joint_limit_nullspace_component()`
- `zero_nullspace_component()`
```

--------------------------------

### pyroboplan.visualization.meshcat_utils

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Utility functions for visualizing robot states, paths, and frames using MeshCat.

```APIDOC
## pyroboplan.visualization.meshcat_utils

### Description
Utility functions for visualization using MeshCat.

### Functions
- `visualize_frame()`
- `visualize_frames()`
- `visualize_path()`
- `visualize_paths()`
```

--------------------------------

### pyroboplan.planning.cartesian_planner

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Implements a Cartesian planner for generating robot trajectories in Cartesian space.

```APIDOC
## pyroboplan.planning.cartesian_planner

### Description
Cartesian planner for generating robot trajectories in Cartesian space.

### Classes
- `CartesianPlanner`
  - `CartesianPlanner.generate()`: Generates a Cartesian path.
- `CartesianPlannerOptions`: Options for configuring the Cartesian planner.
```

--------------------------------

### PolynomialTrajectoryBase.visualize

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.trajectory.html

Visualizes a generated trajectory with one figure window per dimension.

```APIDOC
## visualize

### Description
Visualizes a generated trajectory with one figure window per dimension.

### Parameters
* **dt** (float, optional) - The sample time at which to generate the trajectory by evaluating the polynomial.
* **joint_names** (list[str], optional) - The joint names to use for the figure titles. If unset, uses the text “Dimension 1”, “Dimension 2”, etc.
* **show_position** (bool, optional) - If true, shows the trajectory position values.
* **show_velocity** (bool, optional) - If true, shows the trajectory velocity values.
* **show_acceleration** (bool, optional) - If true, shows the trajectory acceleration values.
* **show_jerk** (bool, optional) - If true, shows the trajectory jerk values.
```

--------------------------------

### DifferentialIk.solve

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.ik.html

Solves an Inverse Kinematics (IK) query using a differential solver. It takes the target frame and its desired transformation as input, and can optionally accept an initial state, nullspace components, and a verbose flag for detailed output.

```APIDOC
## solve

### Description
Solves an IK query.

### Method
DifferentialIk.solve

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
* **target_frame** (str) - The name of the target frame in the model.
* **target_tform** (pinocchio.SE3) - The desired transformation of the target frame in the model.
* **init_state** (array-like, optional) - The initial state to solve from. If not specified, a random initial state will be selected.
* **nullspace_components** (list[function], optional) - An optional list of nullspace components to use when solving. These components must take the form lambda model, q: component(model, q, <other_args>).
* **verbose** (bool, optional) - If True, prints additional information to the console.

### Returns
A list of joint configuration values with the solution, if one was found. Otherwise, returns None.

### Return Type
array-like or None
```

--------------------------------

### PolynomialTrajectoryBase.generate

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.trajectory.html

Generates a full trajectory at a specified sample time.

```APIDOC
## generate

### Description
Generates a full trajectory at a specified sample time.

### Parameters
* **dt** (float) - The sample time, in seconds.

### Returns
The tuple of (t, q, qd, qdd, qddd) trajectory values generated at the sample time. The time vector is 1D, and the others are 2D (time and dimension).

### Return Type
tuple(array-like, array-like, array-like, array-like, array-like)
```

--------------------------------

### pyroboplan.planning.graph

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Provides data structures for representing and manipulating planning graphs, including nodes and edges.

```APIDOC
## pyroboplan.planning.graph

### Description
Data structures for representing and manipulating planning graphs.

### Classes
- `Edge`
  - `Edge.parse()`: Parses an edge from a data source.
- `Graph`
  - `Graph.add_edge()`: Adds an edge to the graph.
  - `Graph.add_node()`: Adds a node to the graph.
  - `Graph.get_nearest_neighbors()`: Retrieves nearest neighbors of a node.
  - `Graph.get_nearest_node()`: Retrieves the nearest node to a given point.
  - `Graph.get_node()`: Retrieves a specific node by its identifier.
  - `Graph.load_from_file()`: Loads a graph from a file.
  - `Graph.remove_edge()`: Removes an edge from the graph.
  - `Graph.remove_node()`: Removes a node from the graph.
  - `Graph.save_to_file()`: Saves the graph to a file.
- `Node`
  - `Node.parse()`: Parses a node from a data source.
```

--------------------------------

### pyroboplan.models.panda.load_point_cloud

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.models.html

Loads a point cloud from a PLY file and converts it into an octree structure.

```APIDOC
## pyroboplan.models.panda.load_point_cloud

### Description
Loads a point cloud from a PLY file and converts it into an octree structure.

### Returns
**octree** – An octree data structure representing the hierarchical spatial partitioning of the point cloud. The voxel resolution default value is set to 0.04 units.

### Return type
coal.Octree
```

--------------------------------

### pyroboplan.ik.differential_ik

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Implements differential inverse kinematics solvers for manipulator control.

```APIDOC
## pyroboplan.ik.differential_ik

### Description
Differential inverse kinematics solvers.

### Classes
- `DifferentialIk`
  - `DifferentialIk.solve()`: Solves the differential inverse kinematics problem.
- `DifferentialIkOptions`: Options for configuring the differential IK solver.
```

--------------------------------

### pyroboplan.models.two_dof

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Functions for loading and configuring collision models for a 2-DOF robot.

```APIDOC
## pyroboplan.models.two_dof

### Description
Functions for loading and configuring collision models for a 2-DOF robot.

### Functions
- `add_object_collisions()`
- `load_models()`
```

--------------------------------

### load_point_cloud

Source: https://pyroboplan.readthedocs.io/en/latest/genindex.html

Loads a point cloud. This function is part of the pyroboplan.models.panda module.

```APIDOC
## load_point_cloud()

### Description
Loads a point cloud.

### Module
pyroboplan.models.panda
```

--------------------------------

### zero_nullspace_component

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.ik.html

Returns a zero nullspace component, which is effectively a no-op. This component returns an array of zeros.

```APIDOC
## zero_nullspace_component

### Description
Returns a zero nullspace component, which is effectively a no-op.

### Parameters
* **model** (pinocchio.Model) – The model from which to generate a random state.
* **q** (array-like) – The joint configuration for the model. Not used, but required to match the function interface.

### Returns
An array of zeros whose length is the number of joint variables in the model.

### Return type
array-like
```

--------------------------------

### CartesianPlanner.generate

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.planning.html

Generates a set of joint trajectories from a Cartesian plan at a specified sample time. It takes an initial joint configuration and a time step as input and returns the success status, time vector, and joint positions.

```APIDOC
## CartesianPlanner.generate

### Description
Generates a set of joint trajectories from the Cartesian plan at a specified sample time.

### Method
`generate(_q_init_, _dt_)`

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
* **q_init** (_array-like_) – The starting joint configuration for the robot. This is used as the initial condition for solving inverse kinematics.
* **dt** (_float_) – The sample time to use for trajectory generation, in seconds.

### Response
#### Success Response
Returns a tuple of (success, t_vec, q_vec) corresponding to a success metric, the vector of times, and vector of joint positions, respectively.

### Return Type
tuple(bool, array-like, array-like)
```

--------------------------------

### get_configuration_from_normalized_path_scaling

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.planning.html

Retrieves a specific joint configuration from a path based on a normalized scaling value. This is useful for interpolating along a path at a precise fractional distance.

```APIDOC
## get_configuration_from_normalized_path_scaling

### Description
Given a path and its corresponding length-normalized scalings between 0.0 and 1.0, get the joint configuration at a specific scale value. For example, 0.0 will return the start configuration of the path, 1.0 will return the end configuration, and 0.5 will return the configuration halfway along the length of the path.

### Parameters
* **q_path** (list[array-like]) – The list of joint configurations describing the path.
* **path_scalings** (list[float]) – The list of scaling values, between 0.0 and 1.0, at each of the path waypoints.
* **value** (float) – The value, between 0.0 and 1.0, at which to get the joint configuration along the path.

### Returns
A tuple containing the joint configuration at the specified scaling value along the path, as well as the index corresponding to the next point along the path.

### Return type
tuple (array-like, int)
```

--------------------------------

### Compute Collisions with Pinocchio

Source: https://pyroboplan.readthedocs.io/en/latest/_sources/motion_planning.rst.txt

Performs collision checking for a given robot configuration using Pinocchio and the Coal library. All collision pairs are activated.

```python
data = model.createData()
collision_data = collision_model.createData()
collision_model.addAllCollisionPairs()
results = pinocchio.computeCollisions(
    model, data, collision_model, collision_data, q, False,
)
```

--------------------------------

### load_ur5_on_base_models

Source: https://pyroboplan.readthedocs.io/en/latest/genindex.html

Loads UR5 on base models. This function is part of the pyroboplan.models.ur5 module.

```APIDOC
## load_ur5_on_base_models()

### Description
Loads UR5 on base models.

### Module
pyroboplan.models.ur5
```

--------------------------------

### load_ur10_on_base_models

Source: https://pyroboplan.readthedocs.io/en/latest/genindex.html

Loads UR10 on base models. This function is part of the pyroboplan.models.ur10 module.

```APIDOC
## load_ur10_on_base_models()

### Description
Loads UR10 on base models.

### Module
pyroboplan.models.ur10
```

--------------------------------

### pyroboplan.models.marble

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Functions for loading and configuring collision models specific to the 'marble' environment.

```APIDOC
## pyroboplan.models.marble

### Description
Functions for loading and configuring collision models for the 'marble' environment.

### Functions
- `add_object_collisions()`
- `load_models()`
```

--------------------------------

### visualize_frames

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.visualization.html

Visualizes multiple coordinate frames as axis triads at specified poses using MeshCat.

```APIDOC
## visualize_frames

### Description
Visualizes a set of coordinate frames as axis triads at specified poses.

### Parameters
- **visualizer** (pinocchio.visualize.meshcat_visualizer.MeshcatVisualizer) – The visualizer instance.
- **prefix_name** (str) – The name of the MeshCat component to add.
- **tforms** (list[pinocchio.SE3]) – A list of transforms at which to display frames.
- **line_length** (float, optional) – The length of the axes in the triad. Defaults to 0.2.
- **line_width** (float, optional) – The width of the axes in the triad. Defaults to 3.
- **line_color** (array-like, optional) – The line colors to use. If None, chooses default axes colors.
```

--------------------------------

### pyroboplan.core.utils.configuration_distance

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.core.html

Calculates the distance between two joint configurations.

```APIDOC
## configuration_distance

### Description
Returns the distance between two joint configurations.

### Parameters
#### Path Parameters
- **q_start** (array-like) – The start joint configuration.
- **q_end** (array-like) – The end joint configuration.

### Returns
The distance between the two joint configurations.

### Return Type
float
```

--------------------------------

### Graph.load_from_file

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.planning.html

Loads a graph structure from a specified file path. This class method reconstructs the Graph object from its saved representation.

```APIDOC
## Graph.load_from_file

### Description
Loads a graph structure from a specified file path. This class method reconstructs the Graph object from its saved representation.

### Method
load_from_file

### Parameters
#### Path Parameters
- **filename** (str) – Required - The full filepath from which to read a Graph.

### Returns
- **pyroboplan.planning.graph.Graph** - The reconstructed Graph from file.
```

--------------------------------

### collision_avoidance_nullspace_component

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.ik.html

Returns a collision avoidance nullspace component. These calculations are based on provided resources for collision-free dynamic locomotion.

```APIDOC
## collision_avoidance_nullspace_component

### Description
Returns a collision avoidance nullspace component based on provided resources.

### Parameters
* **model** (pinocchio.Model) – The model from which to generate a random state.
* **data** (pinocchio.Data) – The model data to use for collision distance checks.
* **collision_model** (pinocchio.GeometryModel) – The model with which to check collision distances.
* **collision_data** (pinocchio.GeometryData) – The collision model data to use for collision distance checks.
* **q** (array-like) – The joint configuration for the model.
* **dist_padding** (float, optional) – The distance padding, in meters, on the collision distances. Defaults to 0.05.
* **gain** (float, optional) – A gain to modify the relative weight of this term. Defaults to 1.0.

### Returns
An array containing the collision avoidance nullspace terms.

### Return type
array-like
```

--------------------------------

### joint_limit_nullspace_component

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.ik.html

Returns a joint limits avoidance nullspace component. This component helps to keep joint configurations away from their limits.

```APIDOC
## joint_limit_nullspace_component

### Description
Returns a joint limits avoidance nullspace component.

### Parameters
* **model** (pinocchio.Model) – The model from which to generate a random state.
* **q** (array-like) – The joint configuration for the model.
* **gain** (float, optional) – A gain to modify the relative weight of this term. Defaults to 1.0.
* **padding** (float, optional) – Optional padding around the joint limits. Defaults to 0.0.

### Returns
An array containing the joint space avoidance nullspace terms.

### Return type
array-like
```

--------------------------------

### get_path_length

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.core.html

Returns the configuration distance of a path.

```APIDOC
## get_path_length

### Description
Returns the configuration distance of a path.

### Parameters
* **q_path** (list[array-like]) – A list of joint configurations describing a path.

### Returns
The total configuration distance of the entire path.

### Return type
float
```

--------------------------------

### CubicPolynomialTrajectory

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.trajectory.html

Describes a cubic (3rd-order) polynomial trajectory.

```APIDOC
## CubicPolynomialTrajectory

### Description
Describes a cubic (3rd-order) polynomial trajectory.

### Parameters
* **_t_** - Start time of the trajectory.
* **_q_** - Start position of the trajectory.
* **_qd** (default: 0.0) - Start velocity of the trajectory.
```

--------------------------------

### joint_limit_nullspace_component

Source: https://pyroboplan.readthedocs.io/en/latest/genindex.html

Calculates the joint limit nullspace component. This function is part of the pyroboplan.ik.nullspace_components module.

```APIDOC
## joint_limit_nullspace_component()

### Description
Calculates the joint limit nullspace component.

### Module
pyroboplan.ik.nullspace_components
```

--------------------------------

### pyroboplan.models.panda

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Functions for loading and configuring collision models for the 'panda' robot, including self-collisions and octree-based collisions.

```APIDOC
## pyroboplan.models.panda

### Description
Functions for loading and configuring collision models for the 'panda' robot.

### Functions
- `add_object_collisions()`
- `add_octree_collisions()`
- `add_self_collisions()`
- `load_models()`
- `load_point_cloud()`
```

--------------------------------

### pyroboplan.trajectory.trajectory_optimization

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.html

Implements trajectory optimization techniques, specifically cubic trajectory optimization, for refining robot movements.

```APIDOC
## pyroboplan.trajectory.trajectory_optimization

### Description
Trajectory optimization methods.

### Classes
- `CubicTrajectoryOptimization`
  - `CubicTrajectoryOptimization.plan()`: Plans an optimized cubic trajectory.
- `CubicTrajectoryOptimizationOptions`: Options for cubic trajectory optimization.
```

--------------------------------

### QuinticPolynomialTrajectory

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.trajectory.html

Describes a quintic (5th-order) polynomial trajectory.

```APIDOC
## QuinticPolynomialTrajectory

### Description
Describes a quintic (5th-order) polynomial trajectory.

### Parameters
* **_t_** - Start time of the trajectory.
* **_q_** - Start position of the trajectory.
* **_qd** (default: 0.0) - Start velocity of the trajectory.
* **_qdd** (default: 0.0) - Start acceleration of the trajectory.
```

--------------------------------

### visualize_frame

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.visualization.html

Visualizes a single coordinate frame as an axis triad at a specified pose using MeshCat.

```APIDOC
## visualize_frame

### Description
Visualizes a coordinate frame as an axis triad at a specified pose.

### Parameters
- **visualizer** (pinocchio.visualize.meshcat_visualizer.MeshcatVisualizer) – The visualizer instance.
- **name** (str) – The name of the MeshCat component to add.
- **tform** (pinocchio.SE3) – The transform at which to display the frame.
- **line_length** (float, optional) – The length of the axes in the triad. Defaults to 0.2.
- **line_width** (float, optional) – The width of the axes in the triad. Defaults to 3.
- **line_color** (array-like, optional) – The line colors to use. If None, chooses default axes colors.
```

--------------------------------

### discretized_joint_space_generator

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.planning.html

Generates samples from the robot's entire joint space with a specified step size. It can optionally continue to yield random samples indefinitely, making it useful for exploration but potentially computationally expensive.

```APIDOC
## discretized_joint_space_generator

### Description
Discretizes the entire joint space of the model at step_size increments. Once the entire space has been returned, the generator can optionally return random samples from the configuration space - in which case this generator will never terminate. This is an extraordinarily expensive operation for high DOF manipulators and small step sizes!

### Parameters
#### Path Parameters
* **model** (pinocchio.Model) - Required - The robot model containing lower and upper position limits.
* **step_size** (float) - Required - The step size for sampling.
* **generate_random** (bool) - Optional - If True, continue randomly sampling the configuration space. Otherwise this generator will terminate.

### Yields
* **np.ndarray** - The next point in the configuration space.
```

--------------------------------

### PolynomialTrajectoryBase.evaluate

Source: https://pyroboplan.readthedocs.io/en/latest/api/pyroboplan.trajectory.html

Evaluates the trajectory at a specific time t.

```APIDOC
## evaluate

### Description
Evaluates the trajectory at a specific time.

### Parameters
* **t** (float) - The time, in seconds, at which to evaluate the trajectory.

### Returns
The tuple of (q, qd, qdd, qddd) trajectory values at the specified time. If the trajectory is single-DOF, these will be scalars, otherwise they are arrays.

### Return Type
tuple(array-like or float, array-like or float, array-like or float, array-like or float)
```
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