1. Biocybernetics and Evolutionary Robotics
- Biocybernetics and Evolutionary Robotics
- Introduction to evolutionary robotics
- Evolution on differential wheeled robots
- Evolution of learning rules
- Biocybernetics - introduction
- Death, intracellular processes and their control
- Genetics, heredity, genetic engineering, biological clock and homeostasis
- Movement, orientation, navigation, communication, homeostat
- ALIFE - Introduction
- Cellular systems
- Selfreplicating cellular systems
- Lindenmayer systems
- Chaos and artificial life
- Game of chaos and iterated functions systems
- Julia and Mandelbrot sets
- Assignments 2012/2013
- Assignments 2011/2012
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1.2. Exam questions
2.1. Introduction to evolutionary robotics
2.2. Evolution on differential wheeled robots
Lecture: Works of Dario Floreano et al.
2.3. Evolution of learning rules
2.4. Biocybernetics - introduction
2.5. Death, intracellular processes and their control
2.6. Genetics, heredity, genetic engineering, biological clock and homeostasis
2.7. Movement, orientation, navigation, communication, homeostat
2.8. ALIFE - Introduction
2.9. Cellular systems
Lecture: Cellular systems
2.10. Selfreplicating cellular systems
Lecture: Selfreplicating cellular systems
2.11. Lindenmayer systems
Lecture: Lindenmayer systems
2.12. Chaos and artificial life
Lecture: Chaos and artificial life
2.13. Game of chaos and iterated functions systems
2.14. Julia and Mandelbrot sets
Lecture: Julia and Mandelbrot sets
3.1. Accessing the sensors of Nao Robot
Example in Python by Michal Havrila (2011):
1 import naoqi 2 import motion 3 import time 4 from msvcrt import getch 5 from naoqi import ALProxy 6 from naoqi import ALBroker 7 from naoqi import ALModule 8 from naoqi import ALBehavior 9 from naoqi import ALDocable 10 IP = "18.104.22.168" # use IP of nao if connecting through lan 11 PORT = 9559 12 proxy = ALProxy('ALMemory',IP,PORT) 13 name1 = "Device/SubDeviceList/RFoot/FSR/FrontLeft/Sensor/Value" 14 name2 = "Device/SubDeviceList/RFoot/FSR/FrontRight/Sensor/Value" 15 16 name3 = "Device/SubDeviceList/RFoot/FSR/RearLeft/Sensor/Value" 17 name4 = "Device/SubDeviceList/RFoot/FSR/RearRight/Sensor/Value" 18 while True: 19 z = getch() 20 result = proxy.getData(name1) 21 print "Value of: ",name1," is: ", result 22 result = proxy.getData(name2) 23 print "Value of: ",name2," is: ", result 24 result = proxy.getData(name3) 25 print "Value of: ",name3," is: ", result 26 result = proxy.getData(name4) 27 print "Value of: ",name4," is: ", result 28 print "" 29 30 time.sleep(1) 31 if z == "s": 32 break
3.2. Capturing visual data from Nao's camera remotely
Examples in Python by Marek Bundzel (2011): Simple capture and save:
1 from naoqi import ALProxy 2 from PIL import Image # comment or install PIL http://www.pythonware.com/products/pil/ 3 4 IP = "22.214.171.124" # use IP of nao if connecting through lan 5 PORT = 9559 6 7 #Create a proxy on the video input module (V.I.M.) 8 camProxy = ALProxy("ALVideoDevice", IP, PORT) 9 10 #Register a Generic Video Module (G.V.M.) to the V.I.M. 11 resolution = 2 # kVGA 12 colorSpace = 11 # kRGB 13 fps = 30 14 nameId = camProxy.subscribe("python_GVM", resolution, colorSpace, fps) 15 camProxy.setColorSpace(nameId,11) 16 17 print nameId 18 19 a = camProxy.getImageRemote(nameId) # returns a list of 7 elements, see NaoRealTimeView.py 20 print len(a) 21 for item in a[:5]: 22 print item 23 print len(a) 24 25 # Comment if you don't have PIL yet 26 b = Image.fromstring("RGB", (a,a), a) # convert to PIL image object 27 b.save("b.jpg") 28 29 #Unregister the G.V.M. 30 camProxy.unsubscribe(nameId)
3.3. Sensors and motion
Example by Jan Adamcak (2011). Nao reacts to objects sensed by the US sensors neuro.py.
4. Assignments 2012/2013
Tracking object in the visual field of the front camera using TLD.
Stabilization while standing on two legs using the force sensors in the feet.
Imitating movement of an object in the Nao's vision field using TLD.
Following Nao (obstacle) in constant distance using sonars.
Nao - Using stereopsis.
Stabilization on one leg using gyrosensor and ankle.
Evolution of the behaviors of tanks in a computer game.
Simulation of game Predator-Prey
Use evolutionary process to optimize the parameters of 2 PID controllers steering the X,Y movement of a hand.
5. Assignments 2011/2012
Tracking the source of sound (turning Nao's head around the Z axis)
Tracking object in the visual field of the front camera using TLD (turning head around Z and X axes)
Stabilization while standing on one leg using the force sensors in the foot. Perturbations by another Nao.
Stabilization while standing on two legs using the force sensors in the feet. Perturbations by another Nao.
Maintaining constant distance from an moving obstacle - another Nao
Imitating movement of an object in the Nao's vision field using TLD
Blocking the ball by Robosoccer