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Paper ThFT4.1

Ghaffari Jadidi, Maani (University of Technology Sydney), Valls Miro, Jaime (University of Technology Sydney), Dissanayake, Gamini (University of Technology Sydney)

Mutual Information-Based Exploration on Continuous Occupancy Maps

Scheduled for presentation during the Regular session "Navigation" (ThFT4), Thursday, October 1, 2015, 16:50−17:05, Saal C1+C2

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sept 28 - Oct 03, 2015, Congress Center Hamburg, Hamburg, Germany

This information is tentative and subject to change. Compiled on July 20, 2019

Keywords Navigation, Mapping, SLAM

Abstract

The problem of active perception with an autonomous robot is studied in this paper. It is proposed that the exploratory behavior of the robot be controlled using mutual information (MI) surfaces between the current map and a one-step look ahead measurements. MI surfaces highlight informative areas for exploration. A novel method for computing these surfaces is described. An approach that exploits structural dependencies of the environment and handles sparse sensor measurements to build a continuous model of the environment, that can then be used to generate MI surfaces is also proposed. A gradient field of occupancy probability distribution is regressed from sensor data as a Gaussian Process and provide frontier boundaries for further exploration. The continuous global frontier surface completely describes unexplored regions and, inherently, provides an automatic stop criterion for a desired sensitivity. The results from publicly available datasets confirm an average improvement of the proposed methodology over comparable standard and state-of-the-art exploratory methods available in the literature by more than 20% and 13% in travel distance and map entropy reduction rate, respectively.

 

 

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