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ElettraSciComp/DStar-Trajectory-Planner

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move_base plugin implementing global trajectory planning with D* informed incremental search algorithm with external optimizers. It strives to simplify development of the robotic systems operating in dense industrial environments.

Overview

The package contains two plugins:

  • D-star trajectory planner that maintains generation of the global trajectory on the provided costmap, and dynamic replanning by request coming from move_base.
  • Virtual Walls module processing JSON objects to generate the non-passable and explicitly passable zones as OpenCV polygons added over the existing map.

Parameters

The plugin accepts the following parameters

Parameter Unit Default value Description
goal_distance_threshold m 0.3 Maximal distance from the chassis' reference frame origin to consider the goal reached
neighbor_distance_threshold m 0.1 The distance to consider as close for replanning
occupancy_threshold - 64 OccupancyGrid cell weight threshold to consider the cell non-passable
cutoff_distance OccupancyGrid cells 16 Maximal cutoff distance for raytracing optimizer
trajectory_optimizer - - Group of parameters to set up the potential field optimizer
trajectory_optimizer/repulsion_gain - 50.0 Gain value for repulsive potential calculation
trajectory_optimizer/potential_field_radius OccupancyGrid cells 10 Maximal repulsion radius to calculate the potential during optimization
erosion - - Group of parameters to set up map preprocessor
erosion/enable - false Applies an erosion algorithm to clean a noisy map
erosion/erosion_gap OccupancyGrid cells 2 Erosion gap

Development and Roadmap

The plugin was developed within the Robotics and Remotization initiative held at Elettra Sincrotrone Trieste. It is a part of an innovative flexible control system for mobile robots that was presented by the group leaders in Tokyo during 16th IFToMM World Congress 2023. The interested ones can find the published paper here: https://doi.org/10.1007/978-3-031-45770-8_29

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