After they had successfully operated the robots, we ran a practical session on 10 and 11 July on "Controlling Robots with Tweets". We presented a quick introduction to natural language processing (using computer programs to analyse human languages, such as English) and provided them with a bundle of software containing a version of the GATE Cloud Twitter Collector modified to run a special GATE application with a custom plugin to use the Java robot library to control the robots.
The bundle came with a simple "gazetteer" containing two lists of keywords:
| left | turn |
|---|---|
| left | turn |
| port | take |
| make | |
| move |
and a basic JAPE grammar (set of rules) to make use of it. JAPE is a specialized programming language used in GATE to match regular expressions over annotations in documents, such as the "Lookup" annotations created whenever the gazetteer finds a matching keyword in a document. (The annotations are similar to XML tags, except that GATE applications can create them as well as read them and they can overlap each other without restrictions. Technically they form an annotation graph.)
The sample rule we provided would match any keyword from the "turn" list followed by any keyword from the "left" list (with optional other words in between, so that "turn to port", "take a left", "turn left" all work the same way) and then run the code to turn the robot's right motor (making it turn left in place).
We showed them how to configure the Twitter Collector, follow their own accounts, and then run the collector with the sample GATE application. Getting the system set up and working took a bit of work, but once the first few groups got their robot to move in response to a tweet, everyone cheered and quickly became more interested. They then worked on extending the word lists and JAPE rules to cover a wider range of tweeted commands.
Some of the students had also developed interesting Java code the previous day, which they wanted to incorporate into the Twitter-controlled system. We helped these students add their code to their own copies of the GATE plugin and re-load it so the JAPE rules could call their procedures.
We first ran this project in the Headstart course in July 2017; we made improvements for this year and it was a success again, so we plan to include it in Headstart 2019 too.
The following maps show where all the students and the female students came from.
This work is supported by the European Union's Horizon 2020 project SoBigData (grant agreement no. 654024). Thanks to Genevieve Gorrell for the diagram illustrating how the system works.
The sample rule we provided would match any keyword from the "turn" list followed by any keyword from the "left" list (with optional other words in between, so that "turn to port", "take a left", "turn left" all work the same way) and then run the code to turn the robot's right motor (making it turn left in place).
We first ran this project in the Headstart course in July 2017; we made improvements for this year and it was a success again, so we plan to include it in Headstart 2019 too.
This work is supported by the European Union's Horizon 2020 project SoBigData (grant agreement no. 654024). Thanks to Genevieve Gorrell for the diagram illustrating how the system works.
