Using Verbal Instructions for Route Learning: Instruction Analysis

Future domestic robots will need to adapt to the special needs of their users and to their environment. It is likely that programming by natural language will be a key method enabling computer language-naïve users to instruct their robots. This paper describes initial steps and considerations towards the design of Instruction-Based Learning (IBL) systems. The proposed methodology is to be tested in the restricted domain of route instructions with real speech input and a real mobile robot using vision for navigation. Users will use unconstrained speech within a restricted domain-specific lexicon determined by analysing a corpus of route instructions. This will maximise speech recognition performance. The robot will possess an appropriate set of primitive procedures that correspond to procedures found in route instructions. Based on 96 route instructions, it is found that the task vocabulary contains approximately 270 words, but is not closed. It increases at an average rate of one new word for every new route instruction, although there are large inter-individual differences. It is also found that 58% of instructions contain no out-of-vocabulary words. The functional vocabulary is found to include 12 different procedures, and is also not closed. It increases at an average rate of one new procedure for every 25 instructions.