1.1 --- a/org/worm_learn.clj	Tue Mar 04 23:04:43 2014 -0500
     1.2 +++ b/org/worm_learn.clj	Sun Mar 16 23:30:32 2014 -0400
     1.3 @@ -14,13 +14,14 @@
     1.4  (dorun (cortex.import/mega-import-jme3))
     1.5  (rlm.rlm-commands/help)
     1.6  
     1.7 +(load-bullet)
     1.8  
     1.9  (def hand "Models/test-creature/hand.blend")
    1.10  
    1.11  (defn worm-model []
    1.12    (load-blender-model "Models/worm/worm.blend"))
    1.13  
    1.14 -(def output-base (File. "/home/r/proj/cortex/render/worm-learn/"))
    1.15 +(def output-base (File. "/home/r/proj/cortex/render/worm-learn/curl"))
    1.16  
    1.17  
    1.18  (defn motor-control-program
    1.19 @@ -40,19 +41,25 @@
    1.20                      effectors
    1.21                      (map #(@current-forces % 0) muscle-positions)))))))
    1.22  
    1.23 +
    1.24 +
    1.25 +
    1.26 +;; These are scripts that direct the worm to move in two radically
    1.27 +;; different patterns -- a sinusoidal wiggling motion, and a curling
    1.28 +;; motions that causes the worm to form a circle.
    1.29 +
    1.30 +(def curl-script
    1.31 +  [[370 :d-up 40]
    1.32 +   [600 :d-up 0]])
    1.33 +
    1.34 +(def period 18)
    1.35 +
    1.36  (def muscle-labels
    1.37    [:base-up :base-down
    1.38     :a-up :a-down
    1.39     :b-up :b-down
    1.40     :c-up :c-down
    1.41 -   :d-up :d-down
    1.42 -   ])
    1.43 -
    1.44 -(def curl-script
    1.45 -  [[370 :d-up 20]
    1.46 -   [390 :d-up 0]])
    1.47 -
    1.48 -(def period 18)
    1.49 +   :d-up :d-down])
    1.50  
    1.51  (defn gen-wiggle [[flexor extensor :as muscle-pair] time-base]
    1.52    (let [period period
    1.53 @@ -63,24 +70,68 @@
    1.54       [(+ time-base (+ (* 2 period) 2))  extensor 0]]))
    1.55    
    1.56  (def wiggle-script
    1.57 -  (mapcat gen-wiggle [[:d-up :d-down]
    1.58 -                      [:c-up :c-down]
    1.59 -                      [:b-up :b-down]
    1.60 -                      [:a-up :a-down]] (range 100 1000 12)))
    1.61 -
    1.62 -(def wiggle-script
    1.63    (mapcat gen-wiggle (repeat 40 [:a-down :a-up])
    1.64                       (range 100 10000 (+ 3 (* period 2)))))
    1.65  
    1.66  
    1.67 +;; Normally, we'd use unsupervised/supervised machine learning to pick
    1.68 +;; out the defining features of the different actions available to the
    1.69 +;; worm. For this project, I am going to explicitely define functions
    1.70 +;; that recognize curling and wiggling respectively. These functions
    1.71 +;; are defined using all the information available from an embodied
    1.72 +;; simulation of the action. Note how much easier they are to define
    1.73 +;; than if I only had vision to work with. Things like scale/position
    1.74 +;; invariance are complete non-issues here. This is the advantage of
    1.75 +;; body-centered action recognition and what I hope to show with this
    1.76 +;; thesis.
    1.77 +
    1.78 +(defn last-nth
    1.79 +  "Create function that will, when called each frame with the senses
    1.80 +   of a creature, will record those results and return the last n
    1.81 +   results."
    1.82 +  [n]
    1.83 +  (let [last-n  '()]
    1.84 +    (fn [frame-num {:keys [touch proprioception muscles hearing]}]
    1.85 +      (take n (cons [frame-num :stuff] last-n)))))
    1.86 +      
    1.87 +
    1.88 +(defn wiggling?
    1.89 +  "Generate a function which, when called each frame with the sensory
    1.90 +   inputs of a worm, will determine whether the worm is wiggling."
    1.91 +  [{:keys [touch proprioception muscles hearing]}]
    1.92 +  (map (fn [f] (f)) proprioception
    1.93 +   
    1.94 +
    1.95 +))
    1.96 +
    1.97 +(defn curling?
    1.98 +  "Is the worm curled up?"
    1.99 +  []
   1.100 +  )
   1.101 +
   1.102 +(defn resting?
   1.103 +  "Is the worm on the ground in a neutral position?"
   1.104 +  [])
   1.105 +
   1.106 +(def standard-world-view
   1.107 +  [(Vector3f. 4.207176, -3.7366982, 3.0816958)
   1.108 +   (Quaternion. 0.11118768, 0.87678415, 0.24434438, -0.3989771)])
   1.109 +
   1.110 +(def worm-side-view
   1.111 +  [(Vector3f. 4.207176, -3.7366982, 3.0816958)
   1.112 +   (Quaternion. -0.11555642, 0.88188726, -0.2854942, -0.3569518)])
   1.113 +
   1.114 +(def degenerate-worm-view
   1.115 +  [(Vector3f. -0.0708936, -8.570261, 2.6487997)
   1.116 +   (Quaternion. -2.318909E-4, 0.9985348, 0.053941682, 0.004291452)])
   1.117  
   1.118  (defn worm-world
   1.119    ""
   1.120    ([] (worm-world curl-script))
   1.121    ([motion-script]
   1.122 -     (let [record? false
   1.123 +     (let [record? false ;;true
   1.124             worm (doto (worm-model) (body!))
   1.125 -           touch   '();;(touch! worm)
   1.126 +           touch   (touch! worm)
   1.127             prop    (proprioception! worm)
   1.128             muscles (movement! worm)
   1.129             
   1.130 @@ -99,19 +150,7 @@
   1.131          
   1.132          (fn [world]
   1.133            ;; (set-gravity world Vector3f/ZERO)
   1.134 -          ;; (position-camera
   1.135 -          ;;  world (Vector3f. 4.207176, -3.7366982, 3.0816958)
   1.136 -          ;;  (Quaternion. 0.11118768, 0.87678415, 0.24434438, -0.3989771))
   1.137 -
   1.138 -
   1.139 -
   1.140 -          (position-camera
   1.141 -           world (Vector3f. 4.207176, -3.7366982, 3.0816958)
   1.142 -           (Quaternion. -0.11555642, 0.88188726, -0.2854942, -0.3569518))
   1.143 -
   1.144 -
   1.145 -
   1.146 -
   1.147 +          (position-camera world degenerate-worm-view)
   1.148            (let [timer (IsoTimer. 60)]
   1.149              (.setTimer world timer)
   1.150              (display-dilated-time world timer))
   1.151 @@ -121,7 +160,6 @@
   1.152               (File. output-base "main-view")))
   1.153            (speed-up world)
   1.154            (light-up-everything world))
   1.155 -        
   1.156          (fn [world tpf]
   1.157            (muscle-display
   1.158             (control-script muscles)