The aim is to develop methods to generate robot programs for the problems in robot learning. The technique that we concentrate on is Genetic Programming.

Robot Learning

• a robot system learns how to perform a task (by trial and error).
• a robot system improves its performance

GP techniques is used to automatically generate robot programs. A robot system requires a program to enable it to perform the task.

Example of a robot program (in VAL II)

; This is plan56 of the chair assembly using the Soma4 parts
;
CALL sinit()
;
CALL zjustz(b4.get, 2)
;
;------- The placing of fork3 -------
CALL zpatget(b4.get, RZ(90), -1.5, 0.5, RZ(0), -1.5, 0.5)
CALL zget(b4.get:RZ(0))
; -- No regrasping required.
CALL zput(b4.put:RZ(-270))
;
. . . .

What is Genetic Programming?

• an unsupervised learning technique
• an optimization technique

How does it work?

1. Generate randomly, solutions as initial population.
2. Evaluate the fitness of individual solution and Select highly fit individuals.
3. Genetic Operation : Recombination, Mutation to generate next generation population.
4. Repeat step 2-3

• In a tree structure


• In a linear form

(IF-AND w+ w+ e+ (IF-AND (IF-NOT (IF-NOT OUT? s- w+) (IF-AND e+ s- e- (IF-OR (IF-NOT w+ s+ e+) s+ e- e-)) (IF-OR (IF-NOT SEE? w- e-) w+ e+ e+)) w- (IF-OR SEE? (IF-OR e- (IF-OR (IF-OR HIT? e+ s+ e-) INC? w- e-) s+ w+) (IF-AND (IF-NOT w- e- e-) w- w- w+) s-) e+)))

• In an encoded form

lbmhhnlfciikaljmmjhimfbehiljmmaegfmimaahajgagngnaacnfiedbddmihclajadh