DistBug path planning algorithm package for ROS Noetic

Algorithms of path-planning in an unknown environment play an important role in robotics.They do not require a prior information about obstacles' locations around a robot and allow calculating a path in a real time.This article presents an implementation of a sensory-based DistBug algorithm, which operates reactively using range data for immediate decision-making without constructing a world model.The algorithm was programmed in Python using robot operating system (ROS) and validated in the Gazebo simulator.For virtual experiments Turtlebot 3 Burger mobile robot was employed.The experiments were conducted in two types of environment: an environment with convex obstacles and a maze.The paper demonstrates analysis of experiments using several standard criteria of a path quality estimation.