The goal of this work is to describe a robotics platform called the Building Wide Intelligence Segbot (segbot). The segbot is a two wheeled robot that can robustly navigate our building, perform obstacle avoidance, and reason about the world. This work has two main goals. First we introduce the segbot platform to anyone that may use it in the future. We begin by examining off-the-shelf components we used and how to build a robot that is able to navigate in a complex multi-floor building environment with moving obstacles. Then we explain the software from a top down viewpoint, with a three layer abstraction model for segmenting code on any robotics platform. The second part of this document describes current work on the segbot platform, which is able to non-robustly take requests for coffee and navigate to a coffee shop while having to move across multiple floors in a building. My contribution to this work is building an infrastructure for multi-floor navigation. The multi-floor infrastructure built is non-robust but has helped identify several issues that will need to be tackled in future iterations of the segbot. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/28533 |
| Date | 17 February 2015 |
| Creators | Unwala, Ali Ishaq |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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