curobo.graph.prm module

class PRMStar( config: GraphConfig, )

Bases: GraphPlanBase

_find_paths( x_init_batch, x_goal_batch, all_paths=False, )

_add_bias_graph( x_init_batch, x_goal_batch, node_set_batch, node_set, )

_find_one_path( x_init_batch, x_goal_batch, )

Find path from a batch of initial and goal configs

Parameters:

x_init ([type]) – batch of start
x_goal ([type]) – batch of goal
return_path_lengths (bool, optional) – [description]. Defaults to False.

Returns:

b, h, dof

Return type:

[type]

_find_all_path( x_init_batch, x_goal_batch, )

Find path from a batch of initial and goal configs

Parameters:

x_init ([type]) – batch of start
x_goal ([type]) – batch of goal
return_path_lengths (bool, optional) – [description]. Defaults to False.

Returns:

b, h, dof

Return type:

[type]

build_graph( x_start=None, x_goal=None, number_of_nodes=None, lazy=False, bias_samples=False, k_nn=5, c_max=10, c_min=1, lazy_nodes=False, )

warmup( x_start: Tensor | None = None, x_goal: Tensor | None = None, )

_add_batch_edges_to_graph( new_nodes, start_nodes, lazy=False, add_exact_node=False, )

_add_unique_nodes_to_graph( nodes, add_exact_node=False, skip_unique_check=False, )

_batch_k_nearest( sample_point, current_graph, k=10, )

_batch_steer( start_nodes, desired_nodes, steer_radius=None, add_steer_pts=-1, lazy=False, )

_batch_steer_and_connect( start_nodes, goal_nodes, add_steer_pts=-1, lazy=False, add_exact_node=False, )

Connect node from start to goal where both are batched.

Parameters:

start_node ([type]) – [description]
goal_nodes ([type]) – [description]

_compute_rotation_frame( x_start, x_goal, )

_cuda_graph_rollout_constraint( x_samples, use_batch_env=False, )

_distance( pt, batch_pts, norm=True, )

_get_graph_shortest_path( start_node_idx, goal_node_idx, return_length=False, )

_hybrid_nearest( sample_node, path, radius, k_n=10, )

_k_nearest( sample_point, current_graph, k=10, )

_mask_samples(x_samples)

_mask_samples_cuda_graph( x_samples, )

_near( sample_point, current_graph, radius, )

_nearest( sample_point, current_graph, )

_sample_pts( n_samples=None, bounded=False, unit_ball=False, seed=123, )

_validate_graph()

add_nodes_to_graph( nodes, add_exact_node=False, )

batch_get_graph_shortest_path( start_idx_list, goal_idx_list, return_length=False, )

batch_path_exists( start_idx_list, goal_idx_list, all_paths=False, )

batch_shortcut_path( g_path, start_idx, goal_idx, )

check_feasibility(x_set)

compute_path_length(path)

connect_nodes( x_set=None, connect_mode='knn', debug=False, lazy=False, add_exact_node=False, k_nn=10, edge_set=None, )

distance( pt, batch_pts, norm=True, )

find_paths( x_init, x_goal, interpolation_steps: int | None = None, ) → GraphResult

static from_dict( graph_dict: Dict, tensor_args: TensorDeviceType, rollout_fn: RolloutBase, safety_rollout_fn: RolloutBase, use_cuda_graph: bool = True, )

get_all_rollout_instances() → List[RolloutBase]

get_biased_vertex_set( x_start, x_goal, c_max=10.0, c_min=1, n=None, lazy=False, )

get_feasible_sample_set( x_samples, )

get_graph()

get_graph_edges()

Return edges in the graph with start node and end node locations

Returns:: tensor

get_graph_shortest_path_lengths( goal_idx: int, )

get_interpolated_trajectory( trajectory: List[Tensor], interpolation_steps: int | None = None, )

get_metrics( state: State, )

get_new_vertex_set( n=None, lazy=False, )

get_node_idx( goal_state, exact=False, ) → int | None

get_path_lengths(goal_idx)

get_paths(path_list)

get_samples( n_samples: int, bounded: bool = True, )

interpolation_acceleration_scale: float = 0.5

interpolation_deviation: float = 0.05

interpolation_dt: float = 0.02

static load_from_robot_config( robot_cfg: str | Dict | RobotConfig, world_model: str | Dict | WorldConfig | None = None, tensor_args: TensorDeviceType = TensorDeviceType(device=device(type='cuda', index=0), dtype=torch.float32, collision_geometry_dtype=torch.float32, collision_gradient_dtype=torch.float32, collision_distance_dtype=torch.float32), world_coll_checker: WorldCollision | None = None, base_cfg_file: str = 'base_cfg.yml', graph_file: str = 'graph.yml', self_collision_check: bool = True, use_cuda_graph: bool = True, seed: int | None = None, )