Path Planning Incorporating Semantic Information for Autonomous Robot Navigation

Abstract

: This paper presents an approach to take into account semantic information for autonomous robot tasks requiring path planning capabilities. A semantic pointcloud or map serves as input for generating a multi-layered map structure, which can then be exploited to address various navigation goals and constraints. Semantic-aware adaptations of A ∗ , Transition-based RRT and a shortcut algorithm are derived in this framework, and evaluated numerically on an exploration and observation task using a reference dataset with multiple semantic classes as an illustrative test environment.