runtime/config/ompl_planning.yml

planner_configs:
  SBLkConfigDefault:
    type: geometric::SBL
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
  ESTkConfigDefault:
    type: geometric::EST
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0 setup()
    goal_bias: 0.05  # When close to goal select goal, with this probability. default: 0.05
  LBKPIECEkConfigDefault:
    type: geometric::LBKPIECE
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
    border_fraction: 0.9  # Fraction of time focused on boarder default: 0.9
    min_valid_path_fraction: 0.5  # Accept partially valid moves above fraction. default: 0.5
  BKPIECEkConfigDefault:
    type: geometric::BKPIECE
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
    border_fraction: 0.9  # Fraction of time focused on boarder default: 0.9
    failed_expansion_score_factor: 0.5  # When extending motion fails, scale score by factor. default: 0.5
    min_valid_path_fraction: 0.5  # Accept partially valid moves above fraction. default: 0.5
  KPIECEkConfigDefault:
    type: geometric::KPIECE
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
    goal_bias: 0.05  # When close to goal select goal, with this probability. default: 0.05
    border_fraction: 0.9  # Fraction of time focused on boarder default: 0.9 (0.0,1.]
    failed_expansion_score_factor: 0.5  # When extending motion fails, scale score by factor. default: 0.5
    min_valid_path_fraction: 0.5  # Accept partially valid moves above fraction. default: 0.5
  RRTkConfigDefault:
    type: geometric::RRT
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
    goal_bias: 0.05  # When close to goal select goal, with this probability? default: 0.05
  RRTConnectkConfigDefault:
    type: geometric::RRTConnect
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
  RRTstarkConfigDefault:
    type: geometric::RRTstar
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
    goal_bias: 0.05  # When close to goal select goal, with this probability? default: 0.05
    delay_collision_checking: 1  # Stop collision checking as soon as C-free parent found. default 1
  TRRTkConfigDefault:
    type: geometric::TRRT
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
    goal_bias: 0.05  # When close to goal select goal, with this probability? default: 0.05
    max_states_failed: 10  # when to start increasing temp. default: 10
    temp_change_factor: 2.0  # how much to increase or decrease temp. default: 2.0
    min_temperature: 10e-10  # lower limit of temp change. default: 10e-10
    init_temperature: 10e-6  # initial temperature. default: 10e-6
    frountier_threshold: 0.0  # dist new state to nearest neighbor to disqualify as frontier. default: 0.0 set in setup()
    frountierNodeRatio: 0.1  # 1/10, or 1 nonfrontier for every 10 frontier. default: 0.1
    k_constant: 0.0  # value used to normalize expresssion. default: 0.0 set in setup()
  PRMkConfigDefault:
    type: geometric::PRM
    max_nearest_neighbors: 10  # use k nearest neighbors. default: 10
  PRMstarkConfigDefault:
    type: geometric::PRMstar
  FMTkConfigDefault:
    type: geometric::FMT
    num_samples: 1000  # number of states that the planner should sample. default: 1000
    radius_multiplier: 1.1  # multiplier used for the nearest neighbors search radius. default: 1.1
    nearest_k: 1  # use Knearest strategy. default: 1
    cache_cc: 1  # use collision checking cache. default: 1
    heuristics: 0  # activate cost to go heuristics. default: 0
    extended_fmt: 1  # activate the extended FMT*: adding new samples if planner does not finish successfully. default: 1
  BFMTkConfigDefault:
    type: geometric::BFMT
    num_samples: 1000  # number of states that the planner should sample. default: 1000
    radius_multiplier: 1.0  # multiplier used for the nearest neighbors search radius. default: 1.0
    nearest_k: 1  # use the Knearest strategy. default: 1
    balanced: 0  # exploration strategy: balanced true expands one tree every iteration. False will select the tree with lowest maximum cost to go. default: 1
    optimality: 1  # termination strategy: optimality true finishes when the best possible path is found. Otherwise, the algorithm will finish when the first feasible path is found. default: 1
    heuristics: 1  # activates cost to go heuristics. default: 1
    cache_cc: 1  # use the collision checking cache. default: 1
    extended_fmt: 1  # Activates the extended FMT*: adding new samples if planner does not finish successfully. default: 1
  PDSTkConfigDefault:
    type: geometric::PDST
  STRIDEkConfigDefault:
    type: geometric::STRIDE
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
    goal_bias: 0.05  # When close to goal select goal, with this probability. default: 0.05
    use_projected_distance: 0  # whether nearest neighbors are computed based on distances in a projection of the state rather distances in the state space itself. default: 0
    degree: 16  # desired degree of a node in the Geometric Near-neightbor Access Tree (GNAT). default: 16
    max_degree: 18  # max degree of a node in the GNAT. default: 12
    min_degree: 12  # min degree of a node in the GNAT. default: 12
    max_pts_per_leaf: 6  # max points per leaf in the GNAT. default: 6
    estimated_dimension: 0.0  # estimated dimension of the free space. default: 0.0
    min_valid_path_fraction: 0.2  # Accept partially valid moves above fraction. default: 0.2
  BiTRRTkConfigDefault:
    type: geometric::BiTRRT
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
    temp_change_factor: 0.1  # how much to increase or decrease temp. default: 0.1
    init_temperature: 100  # initial temperature. default: 100
    frountier_threshold: 0.0  # dist new state to nearest neighbor to disqualify as frontier. default: 0.0 set in setup()
    frountier_node_ratio: 0.1  # 1/10, or 1 nonfrontier for every 10 frontier. default: 0.1
    cost_threshold: 1e300  # the cost threshold. Any motion cost that is not better will not be expanded. default: inf
  LBTRRTkConfigDefault:
    type: geometric::LBTRRT
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
    goal_bias: 0.05  # When close to goal select goal, with this probability. default: 0.05
    epsilon: 0.4  # optimality approximation factor. default: 0.4
  BiESTkConfigDefault:
    type: geometric::BiEST
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
  ProjESTkConfigDefault:
    type: geometric::ProjEST
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
    goal_bias: 0.05  # When close to goal select goal, with this probability. default: 0.05
  LazyPRMkConfigDefault:
    type: geometric::LazyPRM
    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
  LazyPRMstarkConfigDefault:
    type: geometric::LazyPRMstar
  SPARSkConfigDefault:
    type: geometric::SPARS
    stretch_factor: 3.0  # roadmap spanner stretch factor. multiplicative upper bound on path quality. It does not make sense to make this parameter more than 3. default: 3.0
    sparse_delta_fraction: 0.25  # delta fraction for connection distance. This value represents the visibility range of sparse samples. default: 0.25
    dense_delta_fraction: 0.001  # delta fraction for interface detection. default: 0.001
    max_failures: 1000  # maximum consecutive failure limit. default: 1000
  SPARStwokConfigDefault:
    type: geometric::SPARStwo
    stretch_factor: 3.0  # roadmap spanner stretch factor. multiplicative upper bound on path quality. It does not make sense to make this parameter more than 3. default: 3.0
    sparse_delta_fraction: 0.25  # delta fraction for connection distance. This value represents the visibility range of sparse samples. default: 0.25
    dense_delta_fraction: 0.001  # delta fraction for interface detection. default: 0.001
    max_failures: 5000  # maximum consecutive failure limit. default: 5000
  TrajOptDefault:
    type: geometric::TrajOpt

rasms_arm_group:
  planner_configs:
    - SBLkConfigDefault
    - ESTkConfigDefault
    - LBKPIECEkConfigDefault
    - BKPIECEkConfigDefault
    - KPIECEkConfigDefault
    - RRTkConfigDefault
    - RRTConnectkConfigDefault
    - RRTstarkConfigDefault
    - TRRTkConfigDefault
    - PRMkConfigDefault
    - PRMstarkConfigDefault
    - FMTkConfigDefault
    - BFMTkConfigDefault
    - PDSTkConfigDefault
    - STRIDEkConfigDefault
    - BiTRRTkConfigDefault
    - LBTRRTkConfigDefault
    - BiESTkConfigDefault
    - ProjESTkConfigDefault
    - LazyPRMkConfigDefault
    - LazyPRMstarkConfigDefault
    - SPARSkConfigDefault
    - SPARStwokConfigDefault
    - TrajOptDefault