ICRA 2012 Paper Abstract

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Paper TuA01.2

Shen, Shaojie (University of Pennsylvania), Michael, Nathan (University of Pennsylvania), Kumar, Vijay (University of Pennsylvania)

Autonomous Indoor 3D Exploration with a Micro-Aerial Vehicle

Scheduled for presentation during the Regular Session "Estimation and Control for UAVs" (TuA01), Tuesday, May 15, 2012, 08:45−09:00, Meeting Room 1 (Mini-sota)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on December 11, 2017

Keywords Aerial Robotics, Autonomous Navigation, Mapping

Abstract

In this paper, we propose a stochastic differential equation-based exploration algorithm to enable exploration in three-dimensional indoor environments with a payload constrained micro-aerial vehicle (MAV). We are able to address computation, memory, and sensor limitations by considering only the known occupied space in the current map. We determine regions for further exploration based on the evolution of a stochastic differential equation that simulates the expansion of a particle system with Langevin dynamics. The regions of most significant particle expansion correlate to unexplored space. After identifying and processing these regions, the autonomous MAV navigates to these locations to enable fully autonomous exploration. The performance of the approach is demonstrated through numerical simulations and experimental results in single- and multi-floor indoor experiments.

 

 

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