Update README.md

Author: keevindoherty

README.md

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 # Learning-Aided 3D Mapping
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 A suite of algorithms for learning-aided mapping. Includes implementations of Gaussian process regression and Bayesian generalized kernel inference for occupancy prediction using test-data octrees. This framework also contains the components necessary to run OctoMap as a baseline.
 
 ## Overview
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 This implementation as it stands now is primarily intended to enable replication of these methods over a few datasets. In addition to the implementation of relevant learning algorithms and data structures, we provide two sets of range data (sim_structured and sim_unstructured) collected in Gazebo for demonstration. Parameters of the sensors and environments are set in the relevant `yaml` files contained in the `config/datasets` directory, while configuration of parameters for the mapping methods can be found in `config/methods`.
 
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 ```
 
 ## Getting Started
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 ### Dependencies
 
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 ```
 
 ## Running the Demo
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 To run the demo on the `sim_structured` environment, simply run: