1. Introduction To Software Systems ASAP Robotics Software Systems: Lecture 1 Robert Oates MEng rxo@cs.nott.ac.uk Room C85

2. A Brief (and not to scale) History of Robotics Approx. 8 B.C. Science Fiction 1921 Science Fact 1950 Karel Capek’s “robots” “I Robot” 1954 First “universal manipulator” 1961 First production line robot 1990 “Elephants Don’t Play Chess” Legend of Hephaestus The Future Something only half as good as the things foretold in 8 B.C.!!

3. What’s the point of robotics? Industrial –Faster –More efficient –Cheaper in the long run –Can be used in hazardous environments –Distribution of sensors Scientific –Psychology –Sociology –Computer Science

4. Properties of a Robotic System Purposeful Interdisciplinary Complex –All parts need to work, all parts need to work together!

5. Robots as a System Control Software Hardware Environment Robot Real-World Control Signals Actuators Sensory Input Sensor Data

6. Key Issues When Designing a Robotic System Complex Interdisciplinary Good enough to survive in the real world –Dynamic –Noisy –Non-linear Expensive!

7. Software Architectures For Robots : The Bad Old Days GOFAI (Good Old Fashioned AI) –Symbolic AI –Expert Systems etc SMPA (Sense Model Plan Act) Image\Signal Processing –Totally separate research –Not fit for purpose!

8. SMPA SENSE PLAN MODELACT Sensors Actuators ROBOT REAL-WORLD

9. SMPA Sense –Turn real-world signals into data Model –Use data to update an internal model of the world Plan –Plan the best course of action, by manipulating the model Act –Act out the chosen plan, by sending signals back to actuators

10. SMPA & GOFAI : Why didn’t the robot cross the road?

11. Killing Blows For SMPA Slow Model could become out of synchronisation Why waste processor time using a model that is geared to how a human thinks?

12. Elephants Don’t Play Chess (Rodney Brooks, 1990) Symbolism is not the key Don’t blame hardware – blame the architecture!

13. So what do we do now? New controller based on reflexes. –Reactive architectures “The world is its own best model” – Rodney Brooks Complex behaviour Perception ProcessAction

14. So what do we do now? New controller based on reflexes. –Reactive architectures “The world is its own best model” – Rodney Brooks Complex behaviour Laser light taking less time to return than usual on the right If t r < T V r = V r + V offset Robot turns left

15. Reactive Architectures (approximately 1990) Fast enough to process the real-world More biologically feasible Humans do not impose their own models

16. The Robot Lab Located on B Floor of the CSIT Building Facilities –“The robot village” –Pioneer Pen –Robot Football Pitch –5 Pioneer Robots –1 Peoplebot –32 Miabot Pro Swarms –12 Miabot Pros –Lego Robots http://grumpy.cs.nott.ac.uk/~robots/wiki/index.php/Main_Page

17. ASAP and Robotics The Automated Scheduling optimisation And Planning research group Many tasks within robotics, (control, task management) are about optimisation and planning Objectives –Research: Novel control techniques –Don’t want to waste time re-implementing things that are already in the public domain: Procurement!

18. Machine Learning Machine Learning Allows: –Generalisation Neural Networks Repeatedly show training data –Behaviour Modification Reinforcement Learning Repeatedly practice tasks

19. Pioneer Robots – Hardware Structure Pan, tilt and zoom camera Laser range finder Gripper Bumper Switches Wifi Transmitter Rear Sonar Drive Wheel Front Sonar

20. Pioneer Robots – Hardware Structure

21. Standard PC Electronics Sensors & Actuators Serial Port WiFi Robot

22. Pioneer Robots – Commercial Software Operating System: –“Windows” (Microsoft) Control Software: –“ARIA” (MobileRobots) Simulation Software: –“MobileSim” (MobileRobots)

23. Pioneer Robots – Open Source Software Operating System: –Various Linux “Flavours” (types) Control Software: –“Player” Simulation Software: –“Stage”

24. What Do We Use and Why? Operating System: –Linux Real-time Flexible Control Software: –Both! Player ARIA Simulators –More complicated Less resource intensive Guaranteed service time

25. Developing Robot Software

26. Why Use Simulators? Faster –Faster than real-time –This makes many machine learning algorithms possible! Cheaper –Don’t need to build robot Safer –Robot can’t damage people/building/itself –Repeatable Riskier! –The simulator will be different to the real-world

27. Simulators: Capturing the Essence of Reality Simulator Demonstration

28. Ideal Robotic Simulator Simulates noise from sensors Simulates real-world style physics Simulates faster than real time Usable Minimal porting effort NO MATTER HOW GOOD A SIMULATOR IS – THE REAL-WORLD WILL ALWAYS BE DIFFERENT!!

29. Bootstrapping Simulator Training Real-world Training time

30. Cross-Platform Development Many reasons to do so –Preference –Application –Wider Customer Base Many reasons not to! –Compatibility –Complex code “switches” –Porting issues

31. Software Development and Hardware Issues Battery life Mechanical wear Hardware reliability Controlled Environment

32. Key Issues When Implementing a Robotic System Cross-platform development issues Simulator issues Hardware issues

33. Case Study – Pioneer Development ARIA SIGSEG Bug –Driver configuration bugs –Solution: Recompile all code on robots Hardware changes –Solution: Feedback