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ASU 101 Introduction to Robotics and Robotics Programming

ASU 101 Introduction to Robotics and Robotics Programming. Yinong Chen. SCI Faculty in Robotics Computing. Chitta Baral : AI, Autonomous agents, cognitive robotics Subbarao Kambhampati : AI, Automated planning, Machine learning Pat Langley : AI, machine learning

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ASU 101 Introduction to Robotics and Robotics Programming

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  1. ASU 101 Introduction to Robotics and Robotics Programming Yinong Chen

  2. SCI Faculty in Robotics Computing • Chitta Baral: AI, Autonomous agents, cognitive robotics • Subbarao Kambhampati: AI, Automated planning, Machine learning • Pat Langley: AI, machine learning • Yann-Hang Lee: Real-time, embedded systems • W.T. Tsai: Service-oriented robotic computing • Sarma Vrudhula: Embedded systems, power management • Sandeep Gupta: Mobile computing, wireless and embedded sensor networks • Huan Liu: Machine learning, AI, Social computing • Arunabha Sen: Wireless and mobile networks • Winslow Burleson: Human-Computer Interaction • Baoxin Li: Computer vision • Jieping Ye: Machine learning • Dirk Colbry: Robotics, Cognitive science, AI • Yinong Chen: Robotics education

  3. What is a Robot? A robot is a mechanical or virtual artificial agent. It is usually a system, which, by its appearance or movements, conveys a sense that it has intent or agency of its own. [http://en.wikipedia.org/wiki/Robot] Kuka Coroware Robosoft Robotics Connection iRobot Mindstorm NXT

  4. What is a Robot? • Many devices with varying degrees of autonomy are called robots. • Many different definitions for robots exist. • Some consider machines wholly controlled by an operator to be robots. • Others require a machine be easily reprogrammable.

  5. Robot Classes • Manipulators: robotic arms. These are most commonly found in industrial settings. • Mobile Robots: unmanned vehicles capable of locomotion. • Hybrid Robots: mobile robots with manipulators.

  6. Robot Components • Body • Effectors • Actuators • Sensors • Computer hardware • Computer software • Networking and communication

  7. Robot Body • Typically defined as a graph of links and joints:

  8. Types of Joints • A ball joint allows rotation around x, y, and z, • A hinge joint allows rotation around z, • A slider joint, which allows translation along x.

  9. Robot Effectors • Component to accomplish some desired physical functions • Examples: • Hands • Torch • Wheels • Legs

  10. Roomba Effectors

  11. Robot Actuators • Actuators are the “muscles” of the robot. • These can be electric motors, hydraulic systems, pneumatic systems, or any other system that can apply forces to the system.

  12. Robot Sensors Sensors can be active or passive: • Active – derive information from environment’s reaction to robot’s actions, e.g. bumpers and sonar. • Passive – observers only, e.g. cameras and microphones .

  13. Sensor Classes: Ranging sensors • Ranging sensors, such as • sonar, • ultrasonic, • IR, and • laser sensors: • These sensors return the distance to the object. • They typically have two lens (eyes). One sends out a light beam and the other receives the reflected beam. • By measuring the time and angle of reflected beam, as shown in the Figure on the right, the sensors can measure the distance to the object

  14. Sensor Classes: Other Sensors There are many types of sensors • Contact (touch) sensor: A signal is generated when touched • Compass (magnetic) sensor • GPS (Global Positioning System) • Color sensor: return different value for different colors • Temperature sensor Return the temperature • Vehicle accelerometer sensor • Vehicle tire pressure sensor • …

  15. Software Architecture for Robotics Computing • Robotics control methods include deliberative methods and reactive methods. • Deliberative methods are model-driven and involve planning before acting. • Reactive methods is event-driven and behavior must emerge from interaction. • Hybrid architectures are software architectures combining deliberative and reactive controllers.

  16. In Office Outside office Routine of a Medical Professorin Model-Driven Approach Research Consult students Write proposal See ICU patients Teaching Prep Teach a course See out-patients See all in-patients Read reports See ICU patients

  17. Outside office Routine of a Medical Professorin Event-Drive Approach Research Event Board Student questions Student questions Write proposal Student questions Notification Student questions Teaching Prep Answer student questions Student questions Teach a course Alert Board See out-patients ICU patient Read reports Interrupt / Notification ICU patient ICU patient See all in-patients

  18. Model-Driven Programming Main Methods/Services Temperature Exchange rate Breaking News

  19. Main Event-Drive Programming Parallel Activities Control the motors Event Board Sonar sensor Receiving information from base station Temperature sensor Notification Compass sensor Read Sensors Decryption Alert Board Image processing Touch Sensor 1 Interrupt / Notification Touch Sensor 2 Sending information to base station Fire Sensor Encryption

  20. Event-Driven Programming • In computer programming, event-driven programming is a programming paradigm which allows interactions between the computer program and the user or the environment; • The execution flow of the program is determined by • user actions, such as mouse clicks, key presses in GUI programming! • sensor outputs (e.g., touch sensor, motion sensor, etc.), and • messages from other programs

  21. Sensors and Actuators in a Simple Robotics Application

  22. Communication between Activities and Services Event!

  23. Robot Ethics: Three Laws of Robotics Isaac Asimov: A robot may not injure a human being or, through inaction, allow a human being to come to harm. A robot must obey orders given to it by human beings, except where such orders would conflict with the First Law. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

  24. Arizona Robotics ChallengeASU versus UoA http://asusrl.eas.asu.edu/srlab/Research/RoboticsChallenge.html 1 Remote commanded patrolling 4 3 5 2 Floor plan learning Intruder detection Unmanned patrolling and object detection Other Security features, such as fire detection

  25. Game 1: Remote Commanded 16 ft Remote Monitor Station 22 ft 32 ft

  26. Game 2: Floor plan Detection Real map Detected map How similar are they?

  27. Game 3: Object Detection Remote Monitor Station Objects will have minimum dimensions (W,L,H) of 8 inches

  28. Game 4: Intruder Detection Remote Monitor Station

  29. Game 5: Fire Detection Remote Monitor Station

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