LittleYUYU / RobotNavigateNLP

OSU 5522 AI project: navigate robots with natural language instructions

RobotNavigateNLP

OSU 5522 AI project: navigate robots with natural language instructions

Duty	Who	Detail
Program front-end	Shuang Li	front-end presentation of three maps, interaction with back-end model
Process data set	Qi Zhu	processing data into pairs of nl instructions and action sequences, map environment matrices
Code model with TensorFlow	Ziyu Yao	code seq2seq model with environment representation

Dataset

Original dataset

• The original single-sentence MARCO dataset from http://www.cs.utexas.edu/users/ml/clamp/navigation/downloads/LearningNavigationInstructions/.
• Original example in map "Grid":

Instruction	Action sequence
face the octagon carpet	(3, 5, -1), (3, 5, 180)

Data preparation

• Use 0 ~ 4 to represent action "no action", "move forward 1 step", "turn right", "turn left", "turn back" in action sequence. Intial directions are set to 90 degree.
• (x, y, d) is the position (x,y) in maps with facial direction d, where d in {0, 1, 2, 3} corresponds to degree direction {0, 90, 180, 270} respectively.
• Three maps are indexed with number, where 0 = "Grid", 1 = "Jelly", 2 = "L".
• Processed example:

Instruction	Action sequence	Action positions	Map
face the octagon carpet	3	(3, 5, 1), (3, 5, 2)	map0

Map representation

• see seq2seq/map.py
• [x, y, d], d = 0, 90, 180, 270
• x, y表示一个点，d表示方向，0表示右
• [x, y, d] = object(6 * 自前后左右), floor + wall(11 * 前后左右)
• Update: make a 3d matrix for each map of shape [sizeOfX, sizeOfY, 4]. Each element is a 74d vector(implemented with python list). If (x, y, d) doesn't exist in the map, output a zero vector with the same length.

How to use matrix

cd matrix
python
// in python 
import map // at the directory of matrix
map.map_grid
map.map_jelly
map.map_one

Train and decode

Train

rm ../data/data0/checkpoint/* # clean existing checkpoint records
python seq2seq_run.py --size --learning_rate --keep_prob --epoch --num_layer --batch_size --data_dir="../data/data0"

Decode

Interactive decode

python seq2seq_run.py --size --learning_rate --keep_prob --epoch --num_layer --data_dir="../data/data0" --inter_decode=True --batch_size=1 --inter_decode_sent="string_of_instruction" --inter_decode_position="[[1,7,2]]" --inter_decode_map="0"

Decode for testing

python seq2seq_run.py --size --learning_rate --keep_prob --epoch --num_layer --data_dir="../data/data0" --decode=True --decode_dev=True(or --decode_test=True) --batch_size=1