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The problem of path planning in unknown environments remains a challengingproblem - as the environment is gradually observed during the navigation, theunderlying planner has to update the environment representation and replan,promptly and constantly, to account for the new observations. In this paper, wepresent a visibility graph-based planning framework capable of dealing withnavigation tasks in both known and unknown environments. The planner employs apolygonal representation of the environment and constructs the representationby extracting edge points around obstacles to form enclosed polygons. Withthat, the method dynamically updates a global visibility graph using atwo-layered data structure, expanding the visibility edges along with thenavigation and removing edges that become occluded by newly observed obstacles.When navigating in unknown environments, the method is attemptable indiscovering a way to the goal by picking up the environment layout on the fly,updating the visibility graph, and fast re-planning corresponding to the newlyobserved environment. We evaluate the method in simulated and real-worldsettings. The method shows the capability to attempt and navigate throughunknown environments, reducing the travel time by up to 12-47% fromsearch-based methods: A*, D* Lite, and more than 24-35% than sampling-basedmethods: RRT*, BIT*, and SPARS.

FAR Planner: Fast, Attemptable Route Planner using Dynamic Visibility Update