Program Synthesis for Data Structure Conversion in the Autonomous Mobile Industry

Sammanfattning

Interoperability development between Autonomous Mobile Mobots, Auto- mated Guided Vehicles and their fleet managers provided by different brands became a highly important topic in the factory and warehouse management industry. The compatibility between the providers would provide endless opportunities for the customers to build scalable, flexible, and dynamic systems. The thesis develops a program synthesis method that is capable of making conversions between data structures. The results provide the programmers with a tool that can be used to create function compositions by providing input-output pairs and can save a significant amount of time. The study solves the search problem using Context-free grammar and a beam search guided by a neural network. The work compares the performance of three different artificial intelligence structures recurrent neural networks, long short-term memory networks, and gated recurrent unit networks, and validates the solution on a test set that consists of lines from data structures that are used in the Autonomous Mobile Robot industry combined with some generated data to measure performance in regards of the generalization power.