Autonomous Exploration and Semantic Updating of Large-Scale Indoor Environments with Mobile Robots

• URL: http://arxiv.org/abs/2409.15493v1
• Date: Mon, 23 Sep 2024 19:25:03 GMT
• Title: Autonomous Exploration and Semantic Updating of Large-Scale Indoor Environments with Mobile Robots
• Authors: Sai Haneesh Allu, Itay Kadosh, Tyler Summers, Yu Xiang,
• Abstract summary: We introduce a new robotic system that enables a mobile robot to autonomously explore an unknown environment. The robot can semantically map a 93m x 90m floor and update the semantic map once objects are moved in the environment.
• Score: 1.8791971592960612
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We introduce a new robotic system that enables a mobile robot to autonomously explore an unknown environment, build a semantic map of the environment, and subsequently update the semantic map to reflect environment changes, such as location changes of objects. Our system leverages a LiDAR scanner for 2D occupancy grid mapping and an RGB-D camera for object perception. We introduce a semantic map representation that combines a 2D occupancy grid map for geometry, with a topological map for object semantics. This map representation enables us to effectively update the semantics by deleting or adding nodes to the topological map. Our system has been tested on a Fetch robot. The robot can semantically map a 93m x 90m floor and update the semantic map once objects are moved in the environment.

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