Python sample codes and textbook for robotics algorithms.
This report presents the forensic synthetic code analysis of AtsushiSakai/PythonRobotics, a Python project with 30,032 GitHub stars. SynthScan v2.0 examined 37,751 lines of code across 286 source files, recording 228 pattern matches distributed across 9 syntactic categories. The overall adjusted score of 9.8 places this repository in the Low AI signal band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.
Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.
This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.
The scanner identified 228 distinct pattern matches across 9 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | …ing/lqr_speed_steer_control/lqr_speed_steer_control.py | 0 | solve a discrete time_algebraic riccati equation (dare) | STRING |
| HIGH | PathTracking/lqr_steer_control/lqr_steer_control.py | 0 | solve a discrete time_algebraic riccati equation (dare) | STRING |
| HIGH | InvertedPendulum/inverted_pendulum_lqr_control.py | 0 | solve a discrete time_algebraic riccati equation (dare) | STRING |
| HIGH | PathPlanning/LQRPlanner/lqr_planner.py | 0 | solve a discrete time_algebraic riccati equation (dare) | STRING |
| HIGH | …ing/lqr_speed_steer_control/lqr_speed_steer_control.py | 0 | solve the discrete time lqr controller. x[k+1] = a x[k] + b u[k] cost = sum x[k].t*q*x[k] + u[k].t*r*u[k] # ref bertseka | STRING |
| HIGH | PathTracking/lqr_steer_control/lqr_steer_control.py | 0 | solve the discrete time lqr controller. x[k+1] = a x[k] + b u[k] cost = sum x[k].t*q*x[k] + u[k].t*r*u[k] # ref bertseka | STRING |
| HIGH | InvertedPendulum/inverted_pendulum_lqr_control.py | 0 | solve the discrete time lqr controller. x[k+1] = a x[k] + b u[k] cost = sum x[k].t*q*x[k] + u[k].t*r*u[k] # ref bertseka | STRING |
| HIGH | PathPlanning/LQRPlanner/lqr_planner.py | 0 | solve the discrete time lqr controller. x[k+1] = a x[k] + b u[k] cost = sum x[k].t*q*x[k] + u[k].t*r*u[k] # ref bertseka | STRING |
| HIGH | PathPlanning/AStar/a_star.py | 0 | initialize grid map for greedy best-first planning ox: x position list of obstacles [m] oy: y position list of obstacles | STRING |
| HIGH | PathPlanning/BidirectionalAStar/bidirectional_a_star.py | 0 | initialize grid map for greedy best-first planning ox: x position list of obstacles [m] oy: y position list of obstacles | STRING |
| HIGH | PathPlanning/BreadthFirstSearch/breadth_first_search.py | 0 | initialize grid map for greedy best-first planning ox: x position list of obstacles [m] oy: y position list of obstacles | STRING |
| HIGH | …eadthFirstSearch/bidirectional_breadth_first_search.py | 0 | initialize grid map for greedy best-first planning ox: x position list of obstacles [m] oy: y position list of obstacles | STRING |
| HIGH | PathPlanning/DepthFirstSearch/depth_first_search.py | 0 | initialize grid map for greedy best-first planning ox: x position list of obstacles [m] oy: y position list of obstacles | STRING |
| HIGH | PathPlanning/ThetaStar/theta_star.py | 0 | initialize grid map for greedy best-first planning ox: x position list of obstacles [m] oy: y position list of obstacles | STRING |
| HIGH | PathPlanning/Dijkstra/dijkstra.py | 0 | initialize grid map for greedy best-first planning ox: x position list of obstacles [m] oy: y position list of obstacles | STRING |
| HIGH | …ning/GreedyBestFirstSearch/greedy_best_first_search.py | 0 | initialize grid map for greedy best-first planning ox: x position list of obstacles [m] oy: y position list of obstacles | STRING |
| HIGH | PathPlanning/AStar/a_star.py | 0 | theta star path search input: s_x: start x position [m] s_y: start y position [m] gx: goal x position [m] gy: goal y pos | STRING |
| HIGH | PathPlanning/BidirectionalAStar/bidirectional_a_star.py | 0 | theta star path search input: s_x: start x position [m] s_y: start y position [m] gx: goal x position [m] gy: goal y pos | STRING |
| HIGH | PathPlanning/ThetaStar/theta_star.py | 0 | theta star path search input: s_x: start x position [m] s_y: start y position [m] gx: goal x position [m] gy: goal y pos | STRING |
| HIGH | PathPlanning/AStar/a_star.py | 0 | calc grid position :param index: :param min_position: :return: | STRING |
| HIGH | …eadthFirstSearch/bidirectional_breadth_first_search.py | 0 | calc grid position :param index: :param min_position: :return: | STRING |
| HIGH | PathPlanning/BidirectionalAStar/bidirectional_a_star.py | 0 | calc grid position :param index: :param min_position: :return: | STRING |
| HIGH | PathPlanning/ThetaStar/theta_star.py | 0 | calc grid position :param index: :param min_position: :return: | STRING |
| HIGH | PathPlanning/BreadthFirstSearch/breadth_first_search.py | 0 | calc grid position :param index: :param minp: :return: | STRING |
| HIGH | PathPlanning/DepthFirstSearch/depth_first_search.py | 0 | calc grid position :param index: :param minp: :return: | STRING |
| HIGH | …ning/GreedyBestFirstSearch/greedy_best_first_search.py | 0 | calc grid position :param index: :param minp: :return: | STRING |
| HIGH | PathPlanning/LQRRRTStar/lqr_rrt_star.py | 0 | setting parameter start:start position [x,y] goal:goal position [x,y] obstacle_list:obstacle positions [[x,y,size],...] | STRING |
| HIGH | PathPlanning/RRTDubins/rrt_dubins.py | 0 | setting parameter start:start position [x,y] goal:goal position [x,y] obstacle_list:obstacle positions [[x,y,size],...] | STRING |
| HIGH | PathPlanning/RRTStarReedsShepp/rrt_star_reeds_shepp.py | 0 | setting parameter start:start position [x,y] goal:goal position [x,y] obstacle_list:obstacle positions [[x,y,size],...] | STRING |
| HIGH | PathPlanning/RRTStarDubins/rrt_star_dubins.py | 0 | setting parameter start:start position [x,y] goal:goal position [x,y] obstacle_list:obstacle positions [[x,y,size],...] | STRING |
| HIGH | PathPlanning/RRT/rrt_with_sobol_sampler.py | 0 | setting parameter start:start position [x,y] goal:goal position [x,y] obstacle_list:obstacle positions [[x,y,size],...] | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | Mapping/gaussian_grid_map/gaussian_grid_map.py | 19 | def generate_gaussian_grid_map(ox, oy, xyreso, std): | CODE |
| LOW | Mapping/lidar_to_grid_map/lidar_to_grid_map.py | 161 | def generate_ray_casting_grid_map(ox, oy, xy_resolution, breshen=True): | CODE |
| LOW | Mapping/ndt_map/ndt_map.py | 83 | def create_dummy_observation_data(): | CODE |
| LOW | Mapping/ray_casting_grid_map/ray_casting_grid_map.py | 78 | def generate_ray_casting_grid_map(ox, oy, xyreso, yawreso): | CODE |
| LOW⚡ | Mapping/grid_map_lib/grid_map_lib.py | 158 | def calc_grid_index_from_xy_index(self, x_ind, y_ind): | CODE |
| LOW⚡ | Mapping/grid_map_lib/grid_map_lib.py | 162 | def calc_xy_index_from_grid_index(self, grid_ind): | CODE |
| LOW⚡ | Mapping/grid_map_lib/grid_map_lib.py | 166 | def calc_grid_index_from_xy_pos(self, x_pos, y_pos): | CODE |
| LOW⚡ | Mapping/grid_map_lib/grid_map_lib.py | 179 | def calc_grid_central_xy_position_from_grid_index(self, grid_ind): | CODE |
| LOW⚡ | Mapping/grid_map_lib/grid_map_lib.py | 183 | def calc_grid_central_xy_position_from_xy_index(self, x_ind, y_ind): | CODE |
| LOW⚡ | Mapping/grid_map_lib/grid_map_lib.py | 191 | def calc_grid_central_xy_position_from_index(self, index, lower_pos): | CODE |
| LOW⚡ | Mapping/grid_map_lib/grid_map_lib.py | 194 | def calc_xy_index_from_position(self, pos, lower_pos, max_index): | CODE |
| LOW⚡ | Mapping/grid_map_lib/grid_map_lib.py | 201 | def check_occupied_from_xy_index(self, x_ind, y_ind, occupied_val): | CODE |
| LOW | …g/normal_vector_estimation/normal_vector_estimation.py | 66 | def ransac_normal_vector_estimation(points_3d, inlier_radio_th=0.7, | CODE |
| LOW | Mapping/rectangle_fitting/rectangle_fitting.py | 92 | def _calc_closeness_criterion(self, c1, c2): | CODE |
| LOW | Mapping/rectangle_fitting/rectangle_fitting.py | 173 | def _adoptive_range_segmentation(self, ox, oy): | CODE |
| LOW | SLAM/GraphBasedSLAM/graphslam/util.py | 34 | def solve_for_edge_dimensionality(n): | STRING |
| LOW | SLAM/GraphBasedSLAM/graphslam/util.py | 54 | def upper_triangular_matrix_to_full_matrix(arr, n): | STRING |
| LOW | SLAM/ICPMatching/icp_matching.py | 75 | def update_homogeneous_matrix(Hin, R, T): | CODE |
| LOW | SLAM/ICPMatching/icp_matching.py | 90 | def nearest_neighbor_association(previous_points, current_points): | CODE |
| LOW | SLAM/EKFSLAM/ekf_slam.py | 136 | def get_landmark_position_from_state(x, ind): | CODE |
| LOW | SLAM/EKFSLAM/ekf_slam.py | 142 | def search_correspond_landmark_id(xAug, PAug, zi): | CODE |
| LOW | PathTracking/pure_pursuit/pure_pursuit.py | 129 | def pure_pursuit_steer_control(state, trajectory, pind): | CODE |
| LOW | …ing/lqr_speed_steer_control/lqr_speed_steer_control.py | 96 | def lqr_speed_steering_control(state, cx, cy, cyaw, ck, pe, pth_e, sp, Q, R): | CODE |
| LOW | PathTracking/cgmres_nmpc/cgmres_nmpc.py | 66 | def calc_predict_and_adjoint_state(self, x, y, yaw, v, u_1s, u_2s, N, dt): | CODE |
| LOW | PathTracking/cgmres_nmpc/cgmres_nmpc.py | 111 | def _predict_state_with_oylar(x, y, yaw, v, u_1, u_2, dt): | CODE |
| LOW | PathTracking/cgmres_nmpc/cgmres_nmpc.py | 124 | def _adjoint_state_with_oylar(yaw, v, lam_1, lam_2, lam_3, lam_4, u_2, dt): | CODE |
| LOW | …er_control/model_predictive_speed_and_steer_control.py | 223 | def iterative_linear_mpc_control(xref, x0, dref, oa, od): | CODE |
| LOW | …_wheel_feedback_control/rear_wheel_feedback_control.py | 105 | def rear_wheel_feedback_control(state, e, k, yaw_ref): | CODE |
| LOW | tests/test_dubins_path_planning.py | 72 | def test_path_plannings_types(): | CODE |
| LOW | tests/test_rrt_star.py | 22 | def test_no_obstacle_and_robot_radius(): | CODE |
| LOW⚡ | tests/test_frenet_optimal_trajectory.py | 15 | def high_speed_and_merging_and_stopping_scenario_test(): | CODE |
| LOW⚡ | tests/test_frenet_optimal_trajectory.py | 23 | def high_speed_and_velocity_keeping_scenario_test(): | CODE |
| LOW⚡ | tests/test_frenet_optimal_trajectory.py | 31 | def low_speed_and_velocity_keeping_scenario_test(): | CODE |
| LOW⚡ | tests/test_frenet_optimal_trajectory.py | 39 | def low_speed_and_merging_and_stopping_scenario_test(): | CODE |
| LOW | tests/test_distance_map.py | 89 | def test_compute_udf_invalid_input(): | CODE |
| LOW | tests/test_grid_map_lib.py | 28 | def test_xy_and_grid_index_conversion(): | CODE |
| LOW | tests/test_rrt_with_pathsmoothing_radius.py | 6 | def test_smoothed_path_safety(): | CODE |
| LOW | docs/conf.py | 223 | def get_relative_path_from_parent(file_path: str, parent_dir: str): | CODE |
| LOW | InvertedPendulum/inverted_pendulum_lqr_control.py | 116 | def get_numpy_array_from_matrix(x): | CODE |
| LOW | InvertedPendulum/inverted_pendulum_mpc_control.py | 111 | def get_numpy_array_from_matrix(x): | CODE |
| LOW | MissionPlanning/StateMachine/robot_behavior_case.py | 88 | def on_enter_returning_to_base(self): | CODE |
| LOW | MissionPlanning/BehaviorTree/behavior_tree.py | 82 | def not_set_children_raise_error(self): | CODE |
| LOW | MissionPlanning/BehaviorTree/behavior_tree.py | 303 | def not_set_child_raise_error(self): | CODE |
| LOW | MissionPlanning/BehaviorTree/robot_behavior_case.py | 169 | def create_robot_behavior_tree(): | CODE |
| LOW | …thPlanning/ReedsSheppPath/reeds_shepp_path_planning.py | 177 | def left_x_right_left_x_right(x, y, phi): | CODE |
| LOW | …thPlanning/ReedsSheppPath/reeds_shepp_path_planning.py | 345 | def calc_interpolate_dists_list(lengths, step_size): | CODE |
| LOW | …thPlanning/ReedsSheppPath/reeds_shepp_path_planning.py | 427 | def reeds_shepp_path_planning(sx, sy, syaw, gx, gy, gyaw, maxc, step_size=0.2): | CODE |
| LOW | …redictiveTrajectoryGenerator/lookup_table_generator.py | 37 | def search_nearest_one_from_lookup_table(tx, ty, tyaw, lookup_table): | CODE |
| LOW | PathPlanning/BSplinePath/bspline_path.py | 19 | def approximate_b_spline_path(x: list, | CODE |
| LOW | PathPlanning/BSplinePath/bspline_path.py | 66 | def interpolate_b_spline_path(x, y, | CODE |
| LOW | PathPlanning/HybridAStar/hybrid_a_star.py | 182 | def update_node_with_analytic_expansion(current, goal, | CODE |
| LOW | …g/FrenetOptimalTrajectory/frenet_optimal_trajectory.py | 129 | def calc_cartesian_parameters(self, fp, csp): | CODE |
| LOW | …g/FrenetOptimalTrajectory/frenet_optimal_trajectory.py | 175 | def calc_cartesian_parameters(self, fp, csp): | CODE |
| LOW | …g/FrenetOptimalTrajectory/frenet_optimal_trajectory.py | 217 | def calc_cartesian_parameters(self, fp, csp): | CODE |
| LOW | …g/FrenetOptimalTrajectory/frenet_optimal_trajectory.py | 241 | def calc_longitudinal_trajectory(self, c_speed, c_accel, Ti, s0): | CODE |
| LOW | …g/FrenetOptimalTrajectory/frenet_optimal_trajectory.py | 261 | def calc_longitudinal_trajectory(self, c_speed, c_accel, Ti, s0): | CODE |
| LOW | …g/FrenetOptimalTrajectory/frenet_optimal_trajectory.py | 285 | def calc_longitudinal_trajectory(self, c_speed, c_accel, Ti, s0): | CODE |
| LOW | PathPlanning/VisibilityRoadMap/visibility_road_map.py | 49 | def generate_visibility_nodes(self, start_x, start_y, goal_x, goal_y, | CODE |
| LOW | PathPlanning/VisibilityRoadMap/visibility_road_map.py | 71 | def calc_vertexes_in_configuration_space(self, x_list, y_list): | CODE |
| LOW | …ning/TimeBasedPathPlanning/GridWithDynamicObstacles.py | 82 | def generate_dynamic_obstacles(self, obs_count: int) -> list[list[Position]]: | CODE |
| 31 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | Mapping/gaussian_grid_map/gaussian_grid_map.py | 19 | CODE | |
| LOW | Mapping/rectangle_fitting/rectangle_fitting.py | 233 | CODE | |
| LOW | Mapping/rectangle_fitting/rectangle_fitting.py | 126 | CODE | |
| LOW | SLAM/GraphBasedSLAM/graph_based_slam.py | 105 | CODE | |
| LOW | PathTracking/pure_pursuit/pure_pursuit.py | 269 | CODE | |
| LOW | MissionPlanning/BehaviorTree/behavior_tree.py | 196 | CODE | |
| LOW | MissionPlanning/BehaviorTree/behavior_tree.py | 613 | CODE | |
| LOW | …thPlanning/ReedsSheppPath/reeds_shepp_path_planning.py | 287 | CODE | |
| LOW | PathPlanning/AStar/a_star_variants.py | 56 | CODE | |
| LOW | PathPlanning/AStar/a_star_variants.py | 180 | CODE | |
| LOW | PathPlanning/AStar/a_star_variants.py | 267 | CODE | |
| LOW | PathPlanning/AStar/a_star.py | 51 | CODE | |
| LOW | PathPlanning/AStar/a_star.py | 170 | CODE | |
| LOW | PathPlanning/AStar/a_star.py | 189 | CODE | |
| LOW | PathPlanning/AStar/a_star_searching_from_two_side.py | 131 | CODE | |
| LOW | …hPlanning/HybridAStar/dynamic_programming_heuristic.py | 45 | CODE | |
| LOW | …hPlanning/HybridAStar/dynamic_programming_heuristic.py | 120 | CODE | |
| LOW | …hPlanning/HybridAStar/dynamic_programming_heuristic.py | 136 | CODE | |
| LOW | PathPlanning/FlowField/flowfield.py | 46 | CODE | |
| LOW | PathPlanning/FlowField/flowfield.py | 63 | CODE | |
| LOW | …g/FrenetOptimalTrajectory/frenet_optimal_trajectory.py | 450 | CODE | |
| LOW | PathPlanning/BreadthFirstSearch/breadth_first_search.py | 146 | CODE | |
| LOW | PathPlanning/BreadthFirstSearch/breadth_first_search.py | 165 | CODE | |
| LOW | …eadthFirstSearch/bidirectional_breadth_first_search.py | 204 | CODE | |
| LOW | …eadthFirstSearch/bidirectional_breadth_first_search.py | 223 | CODE | |
| LOW | PathPlanning/DStar/dstar.py | 93 | CODE | |
| LOW | PathPlanning/VoronoiRoadMap/dijkstra_search.py | 34 | CODE | |
| LOW | PathPlanning/DepthFirstSearch/depth_first_search.py | 143 | CODE | |
| LOW | PathPlanning/DepthFirstSearch/depth_first_search.py | 162 | CODE | |
| LOW | PathPlanning/VisibilityRoadMap/visibility_road_map.py | 89 | CODE | |
| LOW | …lanning/Eta3SplineTrajectory/eta3_spline_trajectory.py | 199 | CODE | |
| LOW | PathPlanning/TimeBasedPathPlanning/Plotting.py | 53 | CODE | |
| LOW | PathPlanning/TimeBasedPathPlanning/SpaceTimeAStar.py | 27 | CODE | |
| LOW | …ning/TimeBasedPathPlanning/GridWithDynamicObstacles.py | 82 | CODE | |
| LOW | PathPlanning/TimeBasedPathPlanning/SafeInterval.py | 50 | CODE | |
| LOW | PathPlanning/TimeBasedPathPlanning/SafeInterval.py | 102 | CODE | |
| LOW | PathPlanning/InformedRRTStar/informed_rrt_star.py | 44 | CODE | |
| LOW | PathPlanning/BidirectionalAStar/bidirectional_a_star.py | 49 | CODE | |
| LOW | PathPlanning/BidirectionalAStar/bidirectional_a_star.py | 235 | CODE | |
| LOW | PathPlanning/BidirectionalAStar/bidirectional_a_star.py | 254 | CODE | |
| LOW | …anning/WavefrontCPP/wavefront_coverage_path_planner.py | 20 | CODE | |
| LOW | …anning/WavefrontCPP/wavefront_coverage_path_planner.py | 94 | CODE | |
| LOW | …anning/WavefrontCPP/wavefront_coverage_path_planner.py | 113 | CODE | |
| LOW | PathPlanning/ElasticBands/elastic_bands.py | 257 | CODE | |
| LOW | PathPlanning/RRT/sobol/sobol.py | 218 | CODE | |
| LOW | PathPlanning/ThetaStar/theta_star.py | 51 | CODE | |
| LOW | PathPlanning/ThetaStar/theta_star.py | 233 | CODE | |
| LOW | PathPlanning/ThetaStar/theta_star.py | 252 | CODE | |
| LOW | …gTreeCPP/spiral_spanning_tree_coverage_path_planner.py | 36 | CODE | |
| LOW | …gTreeCPP/spiral_spanning_tree_coverage_path_planner.py | 73 | CODE | |
| LOW | …gTreeCPP/spiral_spanning_tree_coverage_path_planner.py | 132 | CODE | |
| LOW | …gTreeCPP/spiral_spanning_tree_coverage_path_planner.py | 154 | CODE | |
| LOW | …gTreeCPP/spiral_spanning_tree_coverage_path_planner.py | 171 | CODE | |
| LOW | …gTreeCPP/spiral_spanning_tree_coverage_path_planner.py | 187 | CODE | |
| LOW | PathPlanning/BugPlanning/bug.py | 14 | CODE | |
| LOW | PathPlanning/BugPlanning/bug.py | 39 | CODE | |
| LOW | PathPlanning/BugPlanning/bug.py | 55 | CODE | |
| LOW | PathPlanning/BugPlanning/bug.py | 116 | CODE | |
| LOW | PathPlanning/BugPlanning/bug.py | 193 | CODE | |
| LOW | …anning/BatchInformedRRTStar/batch_informed_rrt_star.py | 233 | CODE | |
| 17 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | PathTracking/pure_pursuit/pure_pursuit.py | 323 | if not plt.get_fignums(): # Check if window is closed | CODE |
| LOW | tests/test_rrt_with_pathsmoothing_radius.py | 38 | # Check if all points on the smoothed path are safely distant from obstacles | COMMENT |
| LOW | tests/test_move_to_pose.py | 33 | # Check if the speed is changing too much | COMMENT |
| LOW | PathPlanning/TimeBasedPathPlanning/SpaceTimeAStar.py | 96 | # Check if the new node is valid for the next 2 time steps - one step to enter, and another to leave | COMMENT |
| LOW | …ning/TimeBasedPathPlanning/GridWithDynamicObstacles.py | 199 | # Check if position is in grid | COMMENT |
| LOW | …ning/TimeBasedPathPlanning/GridWithDynamicObstacles.py | 203 | # Check if position is not occupied at time t | COMMENT |
| LOW | …rticleSwarmOptimization/particle_swarm_optimization.py | 132 | # Check if start point is inside obstacle | COMMENT |
| LOW | …rticleSwarmOptimization/particle_swarm_optimization.py | 139 | # Check if intersection on segment | COMMENT |
| LOW | …anning/BatchInformedRRTStar/batch_informed_rrt_star.py | 254 | # Check if this can improve the current solution | COMMENT |
| LOW | …anning/BatchInformedRRTStar/batch_informed_rrt_star.py | 534 | # Check if we're at the goal | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | …er_control/model_predictive_speed_and_steer_control.py | 297 | print("Error: Cannot solve mpc..") | CODE |
| LOW | docs/conf.py | 217 | except Exception: | CODE |
| LOW | MissionPlanning/StateMachine/state_machine.py | 291 | except Exception as e: | CODE |
| MEDIUM | MissionPlanning/StateMachine/state_machine.py | 292 | print(f"Error showing PlantUML: {e}") | CODE |
| MEDIUM | PathPlanning/HybridAStar/hybrid_a_star.py | 284 | print("Error: Cannot find path, No open set") | CODE |
| LOW | PathPlanning/ClothoidPath/clothoid_path_planner.py | 76 | except Exception as e: | CODE |
| LOW | PathPlanning/ClothoidPath/clothoid_path_planner.py | 89 | except Exception as e: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | SLAM/GraphBasedSLAM/graphslam/edge/__init__.py | 1 | # Copyright (c) 2020 Jeff Irion and contributors | COMMENT |
| LOW | SLAM/GraphBasedSLAM/graphslam/pose/__init__.py | 1 | # Copyright (c) 2020 Jeff Irion and contributors | COMMENT |
| LOW | PathTracking/move_to_pose/move_to_pose.py | 61 | v : Command linear velocity | COMMENT |
| LOW | docs/conf.py | 1 | # | COMMENT |
| LOW | docs/conf.py | 121 | # Custom sidebar templates, must be a dictionary that maps document names | COMMENT |
| LOW | docs/conf.py | 141 | # The paper size ('letterpaper' or 'a4paper'). | COMMENT |
| LOW | PathPlanning/DStarLite/d_star_lite.py | 381 | # Obstacles discovered at time = row | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | tests/test_distance_map.py | 8 | # Create a simple obstacle map for testing | COMMENT |
| MEDIUM | PathPlanning/ElasticBands/elastic_bands.py | 289 | # Create an elastic band object and optimize | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | SLAM/ICPMatching/icp_matching.py | 8 | CODE | |
| LOW | PathPlanning/RRT/sobol/__init__.py | 1 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …lNavigation/drone_3d_trajectory_following/Quadrotor.py | 12 | CODE |