From 9e30f7ffc040589130995d2c55a4a9003dde5154 Mon Sep 17 00:00:00 2001 From: Steve Macenski Date: Fri, 11 Jun 2021 17:37:12 -0700 Subject: [PATCH] adding smac planner updates --- .../packages/configuring-smac-planner.rst | 255 +++++------------- configuration/packages/smac/path.png | Bin 122370 -> 200922 bytes migration/Galactic.rst | 34 +++ migration/index.rst | 1 + plugins/index.rst | 58 ++-- 5 files changed, 136 insertions(+), 212 deletions(-) create mode 100644 migration/Galactic.rst diff --git a/configuration/packages/configuring-smac-planner.rst b/configuration/packages/configuring-smac-planner.rst index bba08ea5c..d2aecdf76 100644 --- a/configuration/packages/configuring-smac-planner.rst +++ b/configuration/packages/configuring-smac-planner.rst @@ -8,7 +8,8 @@ Source code and README with design, explanations, and metrics can be found on Gi .. _Github: https://github.com/ros-planning/navigation2/tree/main/nav2_smac_planner The Smac Planner plugin implements a 2D A* and Hybrid-A* path planners. -An example of the Hyrid-A* planner can be seen below, planning a 85 meter path in 33ms. +It is important to know that as of June 2021, the planner received a **major** update improving path quality and run-times by 2-3x. +An example of the Hybrid-A* planner can be seen below, planning a 60 meter path in 73ms. Usual planning time is below 100ms for most environments, occasionally up to 200ms. .. image:: smac/path.png :width: 640px @@ -70,7 +71,7 @@ Parameters ==== ======= Type Default ---- ------- - int -1 + int 1000000 ==== ======= Description @@ -85,7 +86,7 @@ Parameters ==== ======= Description - Maximum number of iterations after the search is within tolerance before returning approximate path with best heuristic if exact path not found. + Maximum number of iterations after the search is within tolerance before returning approximate path with best heuristic if exact path not found. 2D only. :````.max_planning_time: @@ -103,33 +104,34 @@ Parameters ====== ======= Type Default ------ ------- - double 2.0 + double 3.5 ====== ======= Description SE2 node will attempt to complete an analytic expansions proportional to this value and the minimum heuristic. -:````.smooth_path: +:````.motion_model_for_search: - ==== ======= - Type Default - ---- ------- - bool False - ==== ======= + ====== ======= + Type Default + ------ ------- + string "DUBIN" + ====== ======= Description - Whether to smooth path with CG smoother. + Motion model enum string to search with. For Hybrid-A* node, default is "DUBIN". For 2D it is "MOORE". Options for SE2 are DUBIN or REEDS_SHEPP. Options for 2D is MOORE and VON_NEUMANN. For state lattice, use STATE_LATTICE. -:````.motion_model_for_search: +:````.cost_travel_multiplier: ====== ======= Type Default ------ ------- - string "DUBIN" + double 2.0 ====== ======= Description - Motion model enum string to search with. For SE2 node, default is "DUBIN". For 2D it is "MOORE". Options for SE2 are DUBIN or REEDS_SHEPP. Options for 2D is MOORE and VON_NEUMANN. + For 2D: Cost multiplier to apply to search to steer away from high cost areas. Larger values will place in the center of aisles more exactly (if non-`FREE` cost potential field exists) but take slightly longer to compute. To optimize for speed, a value of 1.0 is reasonable. A reasonable tradeoff value is 2.0. A value of 0.0 effective disables steering away from obstacles and acts like a naive binary search A*. + :````.angle_quantization_bins: @@ -147,7 +149,7 @@ Parameters ====== ======= Type Default ------ ------- - double 0.2 + double 0.4 ====== ======= Description @@ -169,7 +171,7 @@ Parameters ====== ======= Type Default ------ ------- - double 0.5 + double 0.15 ====== ======= Description @@ -180,7 +182,7 @@ Parameters ====== ======= Type Default ------ ------- - double 1.05 + double 1.50 ====== ======= Description @@ -191,234 +193,121 @@ Parameters ====== ======= Type Default ------ ------- - double 1.2 + double 1.7 ====== ======= Description Heuristic penalty to apply to SE2 node for cost at pose. Allows Hybrid-A* to be cost aware. -:````.smoother.smoother.w_curve: - - ====== ======= - Type Default - ------ ------- - double 1.5 - ====== ======= - - Description - CG smoother cost function weight on the curvature of path. - -:````.smoother.smoother.w_dist: - - ====== ======= - Type Default - ------ ------- - double 0.0 - ====== ======= - - Description - CG smoother cost function weight on the distance from the original path. Disabled by default. - -:````.smoother.smoother.w_smooth: - - ====== ======= - Type Default - ------ ------- - double 15000.0 - ====== ======= - - Description - CG smoother cost function weight on the distance between nodes. - -:````.smoother.smoother.w_cost: - - ====== ======= - Type Default - ------ ------- - double 1.5 - ====== ======= - - Description - CG smoother cost function weight on the costmap's cost. - -:````.smoother.smoother.cost_scaling_factor: - - ====== ======= - Type Default - ------ ------- - double 10.0 - ====== ======= - - Description - Scale factor for the inflation layer. Must be the same as your inflation layer's value. Used to approximate a Voronoi field. - -:````.smoother.optimizer.max_time: - - ====== ======= - Type Default - ------ ------- - double 0.10 - ====== ======= - - Description - Maximum time spent smoothing, in seconds. If planning takes too long, this can be dynamically adjusted to ensure the planner meets ``max_planning_time``. - -:````.smoother.optimizer.max_iterations: - - ====== ======= - Type Default - ------ ------- - int 500 - ====== ======= - - Description - Maximum number of iterations we can run the CG smoother. - -:````.smoother.optimizer.debug_optimizer: - - ====== ======= - Type Default - ------ ------- - bool False - ====== ======= - - Description - Whether to print debug info from Ceres. - -:````.smoother.optimizer.gradient_tol: - - ====== ======= - Type Default - ------ ------- - double 1e-10 - ====== ======= - - Description - Minimum change in gradient to terminate smoothing. - -:````.smoother.optimizer.fn_tol: +:````.lattice_filepath: ====== ======= Type Default ------ ------- - double 1e-7 + string "" ====== ======= Description - Minimum change in function to terminate smoothing. + The filepath to the state lattice graph -:````.smoother.optimizer.param_tol: +:````.lookup_table_size: ====== ======= Type Default ------ ------- - double 1e-15 + double 20.0 ====== ======= Description - Minimum change in parameter blocks to terminate smoothing. + Size of the dubin/reeds-sheep distance window to cache, in meters. -:````.smoother.optimizer.advanced.min_line_search_step_size: +:````.cache_obstacle_heuristic: ====== ======= Type Default ------ ------- - double 1e-20 + bool false ====== ======= Description - Terminate smoothing iteration if change in parameter block less than this. + Cache the obstacle map dynamic programming distance expansion heuristic between subsiquent replannings of the same goal location. Dramatically speeds up replanning performance (40x) if costmap is largely static. -:````.smoother.optimizer.advanced.max_num_line_search_step_size_iterations: +:````.smoother.max_iterations: ====== ======= Type Default ------ ------- - int 50 + int 1000 ====== ======= Description - Maximum iterations for line search in CG smoother. + Cache the obstacle map dynamic programming distance expansion heuristic between subsiquent replannings of the same goal location. Dramatically speeds up replanning performance (40x) if costmap is largely static. -:````.smoother.optimizer.advanced.line_search_sufficient_function_decrease: +:````.smoother.w_smooth: ====== ======= Type Default ------ ------- - double 1e-20 + double 0.3 ====== ======= Description - Function decrease amount to terminate current line search iteration. + Weight for smoother to apply to smooth out the data points -:````.smoother.optimizer.advanced.max_num_line_search_direction_restarts: +:````.smoother.w_data: ====== ======= Type Default ------ ------- - int 10 + double 0.2 ====== ======= Description - Maximum umber of restarts of line search when over-shoots. + Weight for smoother to apply to retain original data information -:````.smoother.optimizer.advanced.max_line_search_step_expansion: +:````.smoother.tolerance: ====== ======= Type Default ------ ------- - int 50 + double 1e-10 ====== ======= Description - Step size multiplier at each iteration of line search. + Parameter tolerance change amount to terminate smoothing session Example ******* .. code-block:: yaml - planner_server: - ros__parameters: - planner_plugins: ["GridBased"] - use_sim_time: True - - GridBased: - plugin: "smac_planner/SmacPlanner" - tolerance: 0.5 # tolerance for planning if unable to reach exact pose, in meters, for 2D node - downsample_costmap: false # whether or not to downsample the map - downsampling_factor: 1 # multiplier for the resolution of the costmap layer (e.g. 2 on a 5cm costmap would be 10cm) - allow_unknown: false # allow traveling in unknown space - max_iterations: -1 # maximum total iterations to search for before failing - max_on_approach_iterations: 1000 # maximum number of iterations to attempt to reach goal once in tolerance, 2D only - max_planning_time: 2.0 # max time in seconds for planner to plan, smooth, and upsample. Will scale maximum smoothing and upsampling times based on remaining time after planning. - smooth_path: false # Whether to smooth searched path - motion_model_for_search: "DUBIN" # 2D Moore, Von Neumann; SE2 Dubin, Redds-Shepp - angle_quantization_bins: 72 # For SE2 node: Number of angle bins for search, must be 1 for 2D node (no angle search) - minimum_turning_radius: 0.20 # For SE2 node & smoother: minimum turning radius in m of path / vehicle - reverse_penalty: 2.1 # For Reeds-Shepp model: penalty to apply if motion is reversing, must be => 1 - change_penalty: 0.20 # For SE2 node: penalty to apply if motion is changing directions, must be >= 0 - non_straight_penalty: 1.05 # For SE2 node: penalty to apply if motion is non-straight, must be => 1 - cost_penalty: 1.3 # For SE2 node: penalty to apply to higher cost zones - - smoother: - smoother: - w_curve: 30.0 # weight to minimize curvature of path - w_dist: 0.0 # weight to bind path to original as optional replacement for cost weight - w_smooth: 30000.0 # weight to maximize smoothness of path - w_cost: 0.025 # weight to steer robot away from collision and cost - cost_scaling_factor: 10.0 # this should match the inflation layer's parameter - - # I do not recommend users mess with this unless they're doing production tuning - optimizer: - max_time: 0.10 # maximum compute time for smoother - max_iterations: 500 # max iterations of smoother - debug_optimizer: false # print debug info - gradient_tol: 1.0e-10 - fn_tol: 1.0e-20 - param_tol: 1.0e-15 - advanced: - min_line_search_step_size: 1.0e-20 - max_num_line_search_step_size_iterations: 50 - line_search_sufficient_function_decrease: 1.0e-20 - max_num_line_search_direction_restarts: 10 - max_line_search_step_expansion: 50 + planner_server: + ros__parameters: + planner_plugins: ["GridBased"] + use_sim_time: True + + GridBased: + plugin: "nav2_smac_planner/SmacPlanner" + tolerance: 0.5 # tolerance for planning if unable to reach exact pose, in meters, for 2D node + downsample_costmap: false # whether or not to downsample the map + downsampling_factor: 1 # multiplier for the resolution of the costmap layer (e.g. 2 on a 5cm costmap would be 10cm) + allow_unknown: false # allow traveling in unknown space + max_iterations: 1000000 # maximum total iterations to search for before failing (in case unreachable), set to -1 to disable + max_on_approach_iterations: 1000 # maximum number of iterations to attempt to reach goal once in tolerance, 2D only + max_planning_time: 3.5 # max time in s for planner to plan, smooth, and upsample. Will scale maximum smoothing and upsampling times based on remaining time after planning. + motion_model_for_search: "DUBIN" # 2D Moore, Von Neumann; Hybrid Dubin, Redds-Shepp; State Lattice set internally + cost_travel_multiplier: 2.0 # For 2D: Cost multiplier to apply to search to steer away from high cost areas. Larger values will place in the center of aisles more exactly (if non-`FREE` cost potential field exists) but take slightly longer to compute. To optimize for speed, a value of 1.0 is reasonable. A reasonable tradeoff value is 2.0. A value of 0.0 effective disables steering away from obstacles and acts like a naive binary search A*. + angle_quantization_bins: 64 # For Hybrid/Lattice nodes: Number of angle bins for search, must be 1 for 2D node (no angle search) + analytic_expansion_ratio: 3.5 # For Hybrid/Lattice nodes: The ratio to attempt analytic expansions during search for final approach. + minimum_turning_radius: 0.40 # For Hybrid/Lattice nodes: minimum turning radius in m of path / vehicle + reverse_penalty: 2.1 # For Reeds-Shepp model: penalty to apply if motion is reversing, must be => 1 + change_penalty: 0.15 # For Hybrid/Lattice nodes: penalty to apply if motion is changing directions, must be >= 0 + non_straight_penalty: 1.50 # For Hybrid/Lattice nodes: penalty to apply if motion is non-straight, must be => 1 + cost_penalty: 1.7 # For Hybrid/Lattice nodes: penalty to apply to higher cost areas when adding into the obstacle map dynamic programming distance expansion heuristic. This drives the robot more towards the center of passages. A value between 1.3 - 3.5 is reasonable. + lattice_filepath: "" # For Lattice node: the filepath to the state lattice graph + lookup_table_size: 20 # For Hybrid/Lattice nodes: Size of the dubin/reeds-sheep distance window to cache, in meters. + cache_obstacle_heuristic: True # For Hybrid/Lattice nodes: Cache the obstacle map dynamic programming distance expansion heuristic between subsiquent replannings of the same goal location. Dramatically speeds up replanning performance (40x) if costmap is largely static. + smoother: + max_iterations: 1000 + w_smooth: 0.3 + w_data: 0.2 + tolerance: 1e-10 diff --git a/configuration/packages/smac/path.png b/configuration/packages/smac/path.png index fc98e7709b16eae856c3ed685714529f9e3c96e7..c33990f346dae38920724daad6bd8605d2ab242b 100644 GIT binary patch literal 200922 zcmXtQ~_w|Dp*Fu9++>2YW;_ei8hv4o~v=H1KiWPTvcP$oNi(7Gf^L*$1WhRqJ z{>nY~oPF0``?DgI6{XNo2vGn40J@B{xGDeudj@^Se?Wx(vSpCE4*h_4`6i?O0s8X& zU={)W4s?~!a#eG%aP=^DHV0VRJAllYT}++L&Fx*R99%Epx`hA$a)6AusJds?X{SPk znUp)t-Fo+g?}bLZI%*ifU4gNWLa}{u+21kIyKT zTiP}ZalplP*3Wz~!VWeQVeWA+iPD$&EfHmNe+nV*AZ#X|UJjeZ8U5|e%5jlPfK5Ba zhwb#ve$$z%F#*@{`=#B9a%X7Tqw8Tue69)fvykL03ei4j*KN8!=JEmDXCKuDz-`krzVo|epOgoHRbhdCxO5==8bKO8bZnn=Dx0yq? zvFHA{V2XdJ>(8pQ=N#%IGe+RX%5fA+cVca$7_!`eD;q}hU_Ylv(?3!Sds@a|JZ5%v z-bT*&N5>0*Xu>f_?faq}lQN}PBv5wG zDlT90U={flv!{!jk|a>Y6tu+qtX<1?Q@>fgrvw5Ni2Tm=(L|db=uNbG*G1O8s{tYKJ 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Planners +*********************************** + +The Smac Planner was significantly improved, of both the 2D and Hybrid-A* implementations, making the paths better, faster, and of higher quality. + + - Collision checker rejects collisions faster and queries the costmap for coordinates less often + - Zero-copy collision checking object + - precompute collision checking footprint orientations so no need for trig at runtime + - Only checking full SE2 footprint when the robot is in the possibly inscribed zones + - Computing the possibly inscribed zones, or the cost over which some part of the footprint may be in collision with a boundary to check the full footprint. Else, check center cost since promised to not be in a potential collision state + - Renaming Hybrid-A* planner to SmacPlannerHybrid + - Precomputing the Reedshepp and Dubin paths offline so at runtime its just a lookup table + - Replacing the wavefront heuristic with a new, and novel, heuristic dubbed the obstacle heuristic. This computes a Dijkstra's path taking into account the 8 connected space, as well as weights for the cost at the positions to guide the heuristic into the center of aisle ways. It also downsamples the costmap such that it can reduce the number of expansions by 75% and have a very small error introduced into the heuristic by being off by at most a partial fraction of a single cell distance + - Improvements to the analytic expansion algorithm to remove the possibility of loops at the end of paths, whenever possible to remove + - 2D A* travel cost and heuristic improvements to speed up planning times and also increase the path quality significantly + - Replaced smoother with a bespoke gradient descent implementation + - Abstract out common utilities of planners into a utils file + - tuned cost functions + - precomputed obstacle heuristic using dynamic programming to expand only the minimum number of nodes + - A caching heuristic setting to enable 25hz planning rates using cached obstacle heuristic values when the goal remains the same + - Leveraging the symmetry in the dubin and reeds-sheep space to reduce cache size by 50% to increase the window size available for heuristic lookup. + - Precompute primitives at all orientation bins + +The tl;dr of these improvements is: + - Plans are 2-3x as fast as they were before, well under 200ms for nearly all situations, making it as fast as NavFn and Global Planner (but now kinematically feasible). Typical planning times are sub-100ms without even making use of the caching or downsampling features. + - Paths are of significantly higher quality via improved smoothers and a novel heuristic that steers the robot towards the center of aisleways implicitly. This makes smoother paths that are also further from obstacles whenever possible. + - Using caching or downsampler parameterizations, can easily achieve path planning with sub-50ms in nearly any sized space. \ No newline at end of file diff --git a/migration/index.rst b/migration/index.rst index 7482acbd9..1508643a5 100644 --- a/migration/index.rst +++ b/migration/index.rst @@ -20,3 +20,4 @@ Navigation2 guides for migration between distributions. Dashing.rst Eloquent.rst Foxy.rst + Galactic.rst diff --git a/plugins/index.rst b/plugins/index.rst index 048e0b8e5..9604e0275 100644 --- a/plugins/index.rst +++ b/plugins/index.rst @@ -96,37 +96,37 @@ Controllers Planners ======== -+-------------------+---------------------------------------+------------------------------+---------------------+ -| Plugin Name | Creator | Description | Drivetrain support | -+===================+=======================================+==============================+=====================+ -| `NavFn Planner`_ | Eitan Marder-Eppstein & Kurt Konolige | A navigation function | Differential, | -| | | using A* or Dijkstras | Omnidirectional, | -| | | expansion, assumes 2D | Legged | -| | | holonomic particle | | -+-------------------+---------------------------------------+------------------------------+---------------------+ -| `SmacPlanner`_ | Steve Macenski | A SE2 Hybrid-A* | **Ackermann**, | -| | | implementation using either | Differential, | -| | | Dubin or Reeds-shepp motion | Omnidirectional, | -| | | models with smoother and | Legged | -| | | multi-resolution query. | | -| | | Cars, car-like, and | | -| | | ackermann vehicles. | | -+-------------------+---------------------------------------+------------------------------+---------------------+ -| `SmacPlanner2D`_ | Steve Macenski | A 2D A* implementation | Differential, | -| | | Using either 4 or 8 | Omnidirectional, | -| | | connected neighborhoods | Legged | -| | | with smoother and | | -| | | multi-resolution query | | -+-------------------+---------------------------------------+------------------------------+---------------------+ -|`ThetaStarPlanner`_| Anshumaan Singh | An implementaion of Theta* | Differential, | -| | | using either 4 or 8 | Omnidirectional | -| | | connected neighborhoods, | | -| | | assumes the robot as a | | -| | | 2D holonomic particle | | -+-------------------+---------------------------------------+------------------------------+---------------------+ ++---------------------------+---------------------------------------+------------------------------+---------------------+ +| Plugin Name | Creator | Description | Drivetrain support | ++===========================+=======================================+==============================+=====================+ +| `NavFn Planner`_ | Eitan Marder-Eppstein & Kurt Konolige | A navigation function | Differential, | +| | | using A* or Dijkstras | Omnidirectional, | +| | | expansion, assumes 2D | Legged | +| | | holonomic particle | | ++---------------------------+---------------------------------------+------------------------------+---------------------+ +| `SmacPlannerHybrid`_ | Steve Macenski | A SE2 Hybrid-A* | **Ackermann**, | +| (formerly `SmacPlanner`) | | implementation using either | Differential, | +| | | Dubin or Reeds-shepp motion | Omnidirectional, | +| | | models with smoother and | Legged | +| | | multi-resolution query. | | +| | | Cars, car-like, and | | +| | | ackermann vehicles. | | ++---------------------------+---------------------------------------+------------------------------+---------------------+ +| `SmacPlanner2D`_ | Steve Macenski | A 2D A* implementation | Differential, | +| | | Using either 4 or 8 | Omnidirectional, | +| | | connected neighborhoods | Legged | +| | | with smoother and | | +| | | multi-resolution query | | ++---------------------------+---------------------------------------+------------------------------+---------------------+ +|`ThetaStarPlanner`_ | Anshumaan Singh | An implementaion of Theta* | Differential, | +| | | using either 4 or 8 | Omnidirectional | +| | | connected neighborhoods, | | +| | | assumes the robot as a | | +| | | 2D holonomic particle | | ++---------------------------+---------------------------------------+------------------------------+---------------------+ .. _NavFn Planner: https://github.com/ros-planning/navigation2/tree/main/nav2_navfn_planner -.. _SmacPlanner: https://github.com/ros-planning/navigation2/tree/main/nav2_smac_planner +.. _SmacPlannerHybrid: https://github.com/ros-planning/navigation2/tree/main/nav2_smac_planner .. _SmacPlanner2D: https://github.com/ros-planning/navigation2/tree/main/nav2_smac_planner .. _ThetaStarPlanner: https://github.com/ros-planning/navigation2/tree/main/nav2_theta_star_planner