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This paper solves the planar navigation problem by recourse to an onlinereactive scheme that exploits recent advances in SLAM and visual objectrecognition to recast prior geometric knowledge in terms of an offlinecatalogue of familiar objects. The resulting vector field planner guaranteesconvergence to an arbitrarily specified goal, avoiding collisions along the waywith fixed but arbitrarily placed instances from the catalogue as well ascompletely unknown fixed obstacles so long as they are strongly convex and wellseparated. We illustrate the generic robustness properties of suchdeterministic reactive planners as well as the relatively modest computationalcost of this algorithm by supplementing an extensive numerical study withphysical implementation on both a wheeled and legged platform in differentsettings.

Reactive Navigation in Partially Familiar Planar Environments Using Semantic Perceptual Feedback