Adds initial 'moveit_setup_assistant' panda config

.setup_assistant

@@ -0,0 +1,11 @@
+moveit_setup_assistant_config:
+  URDF:
+    package: franka_description
+    relative_path: robots/panda_arm.urdf.xacro
+    xacro_args: hand:=true
+  SRDF:
+    relative_path: config/panda.srdf
+  CONFIG:
+    author_name: Rick Staa
+    author_email: [email protected]
+    generated_timestamp: 1628762938

CMakeLists.txt

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+cmake_minimum_required(VERSION 3.1.3)
+project(panda_moveit_config)
+
+find_package(catkin REQUIRED)
+
+catkin_package()
+
+install(DIRECTORY launch DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}
+  PATTERN "setup_assistant.launch" EXCLUDE)
+install(DIRECTORY config DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION})

config/cartesian_limits.yaml

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+cartesian_limits:
+  max_trans_vel: 1
+  max_trans_acc: 2.25
+  max_trans_dec: -5
+  max_rot_vel: 1.57

config/chomp_planning.yaml

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+planning_time_limit: 10.0
+max_iterations: 200
+max_iterations_after_collision_free: 5
+smoothness_cost_weight: 0.1
+obstacle_cost_weight: 1.0
+learning_rate: 0.01
+smoothness_cost_velocity: 0.0
+smoothness_cost_acceleration: 1.0
+smoothness_cost_jerk: 0.0
+ridge_factor: 0.01
+use_pseudo_inverse: false
+pseudo_inverse_ridge_factor: 1e-4
+joint_update_limit: 0.1
+collision_clearance: 0.2
+collision_threshold: 0.07
+use_stochastic_descent: true
+enable_failure_recovery: true
+max_recovery_attempts: 5

config/fake_controllers.yaml

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+controller_list:
+  - name: fake_panda_arm_controller
+    type: $(arg execution_type)
+    joints:
+      - panda_joint1
+      - panda_joint2
+      - panda_joint3
+      - panda_joint4
+      - panda_joint5
+      - panda_joint6
+      - panda_joint7
+  - name: fake_hand_controller
+    type: $(arg execution_type)
+    joints:
+      - panda_finger_joint1
+initial:  # Define initial robot poses.
+  - group: panda_arm
+    pose: ready
+  - group: hand
+    pose: open

config/joint_limits.yaml

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+# joint_limits.yaml allows the dynamics properties specified in the URDF to be overwritten or augmented as needed
+
+# For beginners, we downscale velocity and acceleration limits.
+# You can always specify higher scaling factors (<= 1.0) in your motion requests.  # Increase the values below to 1.0 to always move at maximum speed.
+default_velocity_scaling_factor: 0.1
+default_acceleration_scaling_factor: 0.1
+
+# Specific joint properties can be changed with the keys [max_position, min_position, max_velocity, max_acceleration]
+# Joint limits can be turned off with [has_velocity_limits, has_acceleration_limits]
+joint_limits:
+  panda_finger_joint1:
+    has_velocity_limits: true
+    max_velocity: 0.2
+    has_acceleration_limits: false
+    max_acceleration: 0
+  panda_finger_joint2:
+    has_velocity_limits: true
+    max_velocity: 0.2
+    has_acceleration_limits: false
+    max_acceleration: 0
+  panda_joint1:
+    has_velocity_limits: true
+    max_velocity: 2.175
+    has_acceleration_limits: false
+    max_acceleration: 0
+  panda_joint2:
+    has_velocity_limits: true
+    max_velocity: 2.175
+    has_acceleration_limits: false
+    max_acceleration: 0
+  panda_joint3:
+    has_velocity_limits: true
+    max_velocity: 2.175
+    has_acceleration_limits: false
+    max_acceleration: 0
+  panda_joint4:
+    has_velocity_limits: true
+    max_velocity: 2.175
+    has_acceleration_limits: false
+    max_acceleration: 0
+  panda_joint5:
+    has_velocity_limits: true
+    max_velocity: 2.61
+    has_acceleration_limits: false
+    max_acceleration: 0
+  panda_joint6:
+    has_velocity_limits: true
+    max_velocity: 2.61
+    has_acceleration_limits: false
+    max_acceleration: 0
+  panda_joint7:
+    has_velocity_limits: true
+    max_velocity: 2.61
+    has_acceleration_limits: false
+    max_acceleration: 0

config/kinematics.yaml

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+panda_arm:
+  kinematics_solver: kdl_kinematics_plugin/KDLKinematicsPlugin
+  kinematics_solver_search_resolution: 0.005
+  kinematics_solver_timeout: 0.005

config/ompl_planning.yaml

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+planner_configs:
+  AnytimePathShortening:
+    type: geometric::AnytimePathShortening
+    shortcut: true  # Attempt to shortcut all new solution paths
+    hybridize: true  # Compute hybrid solution trajectories
+    max_hybrid_paths: 24  # Number of hybrid paths generated per iteration
+    num_planners: 4  # The number of default planners to use for planning
+    planners: ""  # A comma-separated list of planner types (e.g., "PRM,EST,RRTConnect"Optionally, planner parameters can be passed to change the default:"PRM[max_nearest_neighbors=5],EST[goal_bias=.5],RRT[range=10. goal_bias=.1]"
+  SBL:
+    type: geometric::SBL
+    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
+  EST:
+    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
+  LBKPIECE:
+    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
+  BKPIECE:
+    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
+  KPIECE:
+    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
+  RRT:
+    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
+  RRTConnect:
+    type: geometric::RRTConnect
+    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
+  RRTstar:
+    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
+  TRRT:
+    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()
+  PRM:
+    type: geometric::PRM
+    max_nearest_neighbors: 10  # use k nearest neighbors. default: 10
+  PRMstar:
+    type: geometric::PRMstar
+  FMT:
+    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
+  BFMT:
+    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
+  PDST:
+    type: geometric::PDST
+  STRIDE:
+    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
+  BiTRRT:
+    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
+  LBTRRT:
+    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
+  BiEST:
+    type: geometric::BiEST
+    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
+  ProjEST:
+    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
+  LazyPRM:
+    type: geometric::LazyPRM
+    range: 0.0  # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
+  LazyPRMstar:
+    type: geometric::LazyPRMstar
+  SPARS:
+    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
+  SPARStwo:
+    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
+panda_arm:
+  planner_configs:
+    - AnytimePathShortening
+    - SBL
+    - EST
+    - LBKPIECE
+    - BKPIECE
+    - KPIECE
+    - RRT
+    - RRTConnect
+    - RRTstar
+    - TRRT
+    - PRM
+    - PRMstar
+    - FMT
+    - BFMT
+    - PDST
+    - STRIDE
+    - BiTRRT
+    - LBTRRT
+    - BiEST
+    - ProjEST
+    - LazyPRM
+    - LazyPRMstar
+    - SPARS
+    - SPARStwo
+hand:
+  planner_configs:
+    - AnytimePathShortening
+    - SBL
+    - EST
+    - LBKPIECE
+    - BKPIECE
+    - KPIECE
+    - RRT
+    - RRTConnect
+    - RRTstar
+    - TRRT
+    - PRM
+    - PRMstar
+    - FMT
+    - BFMT
+    - PDST
+    - STRIDE
+    - BiTRRT
+    - LBTRRT
+    - BiEST
+    - ProjEST
+    - LazyPRM
+    - LazyPRMstar
+    - SPARS
+    - SPARStwo