week0 on robotics of human kind by journal.ppt
- 1. Autonomous Robots CS 393R Professor: Peter Stone TA: Katie Genter
- 2. Robots Slides Courtesy of Benjamin Kuipers
- 3. Robots
- 4. Robots
- 5. What is a robot? • A robot is an intelligent system that interacts with the physical environment through sensors and effectors. – Program module? – Web crawling ‘bot? Robot Environment sensors effectors
- 6. Slide by Manuela Veloso (on web)
- 7. Is a human a robot? • By our definition, yes. – Humans interact with a complex physical environment via sensors and effectors. – We are not artificially manufactured, of course! • Does this diminish humans? No! – Understanding the difficulties of robotics helps us appreciate how amazing humans are.
- 8. We will study robots that … • … function in (mostly) unmodified human environments. – (Well, in soccer fields, anyway.) • … that use, and perhaps even learn, useful models of the environment. – They have knowledge, and act on it.
- 9. What makes a good model of the environment? • A good model is a simplified description of the environment such that … – If the robot orients itself in the model, – and makes a plan using the model, – and executes that plan in the real environment, – then the plan has its intended effect.
- 10. What will we do in this course? • Our goal is to learn some methods for implementing this interactive loop. • We will spend a few weeks each on topics that often get entire graduate courses. Robot Environment sensors effectors
- 11. Subject Material Areas • Motion and Control (action) – PID control, open/closed loop control, action modeling, walking, ... • Sensing and Perception (perception) – Range sensing, vision, filtering, sensor modeling, ... • Decision Making (cognition) – Behavior architectures, planning, AI, developmental psychology, ...
- 12. Major Topics and Projects • What is robotics? • Control theory • Observers and tracking • Localization • Vision • Behavior • Applications • Social implications • “Hello, World!” (9/8) • Motor control (9/22) • Kalman filter (10/6) • Localization (10/20) • Vision (11/3) • Final projects (11/29) – Proposal (10/27) – Literature survey (11/10) – Demonstration (12/1) Official Syllabus online
- 13. Control Laws and Behaviors • Rules for behaving in a qualitatively uniform environment. – Following walls, seeking open space or targets. • Rich theory based on differential equations and dynamical systems. • Reality outside the model is treated as noise. • Compose multiple control laws to make behaviors. • Task: Approach and kick a ball to a target.
- 14. Observers • Sensors don’t sense the world directly. – They just respond to its stimulation. • By gathering lots of sensor input over time, we can estimate what the world is like. • Assumes models of the nature of the world, and of sensor properties, such as error types. • Task: Implement Kalman Filters to track and block a rolling ball.
- 15. Social Implications • Robots may change our world dramatically – How? For better? Or for worse? • Science fiction writers have thought about a lot of important possibilities. • We will read and discuss a few. – Brief discussion. Few conclusions. – Questions are more important than answers.
- 16. Robot Lab Assignments • There are five robot lab assignments. – Due every two weeks. • You demonstrate the techniques taught in class. – “In theory, there’s no difference between theory and practice, but in practice, there is.”
- 17. Robot Assignments 1, 2, 3 • Students will work in teams. – Each team has two people. – A single grade for each team. • Each team has one physical robot – an Aibo. – These are expensive, fragile, and irreplaceable! – Take care of them!
- 18. Robot Assignments 4, 5 • Under revision – will use the Nao robots • Probably still in pairs • Some parts in simulation – may be done individually. • Localization and vision.
- 19. The 1st robot: Sony AIBO • Several sensors • 20 degrees of freedom • Onboard computing
- 20. Entertainment Robot System 7 • Sony designed the AIBO as an entertainment robot, with sophisticated built-in behaviors. – We won’t be using those. – You are welcome to explore them, but that’s not part of the course. • We are using the AIBO as a platform for implementing robotic capabilities.
- 21. Technical Details • CPU: 64 bit RISC – 64 mb RAM • LAN: 802.11b • Degrees of freedom: – Head: 3 dof – Mouth 1 dof – Legs: 3 dof x 4 – Ears: 1 dof x 2 – Tail: 2 dof • Image input: – 350,000 pixel CMOS camera • Stereo microphones • Infrared distance x 2 • Acceleration • Vibration • Touch: head, back, chin, paw
- 22. Shooting and Blocking Past year's example videos...
- 23. What Assignments Require • The point of the assignments is to implement the methods taught in class. • To turn in an assignment: – Demonstrate the behavior to Katie before the due date. – Each team hands in a clear, concise memo describing the problem, your approach, and your results. • Append the code. – The memo describes the role of each individual on the team in accomplishing this assignment. • We will discuss each assignment in class on the due date. – Some teams will be selected to demonstrate the robots. – No assignments accepted after that class meeting.
- 24. Working in Teams • One of the goals of this course is to give you experience at working in teams. – Robot assignments 1, 2, and 3 – likely 4 & 5. • Your team can be stronger than any one individual, but it is also vulnerable. • You are responsible for working effectively with your team – not just for doing your own job, but also – for helping the team work well together.
- 25. Final Projects • Research one topic in greater depth. • Select a research goal (suggestions to be provided). • Survey the related literature. • Implement a prototype system and/or experiment. • Describe in detail what you did, how it worked out, what alternative approaches were.
- 26. Grading • Robot Assignments – Hello, World! (10%) – Kicking (10%) – Tracking (10%) – Localization (10%) – Vision (10%) • These are never accepted late! • Participation (10%) • Reading responses – Due night before class – (10%) • Projects (30%) – Proposal – Literature – Presentation – Report
- 27. This class is a lot of work. • Robotics includes many different concepts. – Control theory, logic, probability, search, etc. • Abstraction barriers are very strong in most of Computer Science, but weak in Robotics. – Programs are vulnerable to sensor and motor glitches. • Plan ahead, to put the time in to this course. – Your team will be depending on you.
- 28. Robotics • The topic is fundamentally important scientifically and technologically. – Building intelligent agents – Modeling the phenomenon of mind • It will be very demanding on all of us. – Be prepared, and start work early. • It’s also very exciting and lots of fun! First assignment: Join mailing list TODAY! Read and react to control tutorial by Mon.