CS494/594: Software for Intelligent Robotics

Transcription

1 CS494/594: Software for Intelligent Robotics Spring 2007 Tuesday/Thursday 11:10 12:25 Instructor: Dr. Lynne E. Parker TA: Rasko Pjesivac

2 Outline Overview syllabus and class policies Introduction to class: what we ll study and what we won t study Overview of assignment #1: Introduction to robotic simulator

3 Overview of Syllabus and Class Policies (See handout)

4 What is a Robot? Notion derives from 2 strands of thought: Humanoids -- human-like Automata -- self-moving things Robot -- derives from Czech word robota Robota : forced work or compulsory service Term coined by Czech playright Karel Capek 1921 play R.U.R (Rossum s Universal Robots ) Current notion of robot: Programmable Mechanically capable Flexible Our working definition of robot: physical agent that generates intelligent connection between perception and action

5 State of Robotics Applications Moving from manufacturing, industrial manipulators to: Entertainment robotics Personal service robots Medical robots Industrial applications beyond factory (e.g., mining, agriculture) Hazardous applications (e.g., military, toxic cleanup, space)

6 Some Current Robots Humanoid robots Manipulator/ Industrial robots Service robots

7 More Robots Wheeled robots Tracked robots Swimming robots Flying robots Legged robots

8 And even more robots Entertainment robots Modular/reconfigurable robots

9 Robots: Alternative Terms UAV unmanned aerial vehicle UGV (rover) unmanned ground vehicle UUV unmanned undersea vehicle

10 Robots: Hollywood Fiction vs. Real-World Fact Hollywood Robots: Human-like capabilities Sense all, know all Real-World Robots: Insect or simple animal capabilities Sense little, know little Ariel mine clearer Rosie the robot Star Wars Robots Robby the Robot Industrial manipulator Hospital delivery robot

11 What is in a Robot? Sensors Effectors and actuators Used for locomotion and manipulation Controllers for the above systems Coordinating information from sensors with commands for the robot s actuators Robot = an autonomous system which exists in the physical world, can sense its environment and can act on it to achieve some goals

12 What are Basic Robot Software Issues? Perception Control Action (sense/detect) (behave, plan, react, reason, ) Environment (through effectors: wheels, legs, tracks, ) How do you perceive? How do you control? How to you generate action?

13 Challenges Perception Limited, noisy sensors Actuation Limited capabilities of robot effectors Thinking Time consuming in large state spaces Environments Dynamic, impose fast reaction times

14 Uncertainty Uncertainty is a key property of existence in the physical world Environment is stochastic and unpredictable Physical sensors provide limited, noisy, and inaccurate information Physical effectors produce limited, noisy, and inaccurate action Models are simplified and inaccurate

15 Uncertainty (cont.) A robot cannot accurately know the answers to the following: Where am I? Where are my body parts, are they working, what are they doing? What did I just do? What will happen if I do X? Who/what are you, where are you, what are you doing, etc.?... Example: (pictures from Thrun, CMU)

16 Classical activity decomposition Locomotion (moving around, going places) factory delivery, Mars Pathfinder, lawnmowers, vacuum cleaners... Manipulation (handling objects) factory automation, automated surgery... This divides robotics into two basic areas mobile robotics manipulator robotics but these are merging in domains like robot pets, robot soccer, and humanoids

17 Focus this Semester: Software for Intelligent Robotics Impressive recent progress in robotic hardware Current bottleneck : Intelligent software From issue of Communications of the ACM (March 02), special issue on Robots: Intelligence, Versatility, Adaptivity : A key challenge is designing algorithms that allow robots to function autonomously in unstructured, dynamic, partially observable, and uncertain environments.

18 Software for Intelligent Robotics Software issues enabling autonomous mobile robots to accomplish given objectives in unstructured, dynamic, partially observable, and uncertain environments: Autonomous: robot makes majority of decisions on its own; no human-inthe-loop control (as opposed to teleoperated) Mobile: robot does not have fixed based (e.g., wheeled, as opposed to manipulator arm) Unstructured: environment has not been specially designed to make robot s job easier Dynamic:environment may change unexpectedly Partially observable: robot cannot sense entire state of the world (i.e., hidden states) Uncertain:sensor readings are noisy; effector output is noisy

19 Example Robot Systems (Movies)

20 What we ll study Robot control architectures Biological foundations Design of behavior-based systems Representation Issues Sensing Adaptation Multi-robot systems Path planning Navigation Localization Mapping

21 What we won t study Kinematics and dynamics: this is covered in mechanical engineering Teleoperated systems: this is covered in mechanical engineering Traditional robotic control theory: this is covered in electrical engineering Theory of mind, cognitive systems, etc.: this is covered in psychology, cognitive science We ll instead focus on computer science issues: algorithm development, artificial intelligence, software design, etc.

22 Assignment #1: Getting familiar with Player/Stage Simulator The Player-Stage-Gazebo simulator (playerstage.sourceforge.net) Player is a general purpose language-independent network server for robot control Stage is a Player-compatible high-fidelity indoor multi-robot simulation testbed Gazebo is a Player-compatible high-fidelity 3D outdoor simulation testbed with dynamics Player/Stage/Gazebo allows for direct porting to Player-compatible physical robots. For high-level intro, see: Most Valuable Player: A Robot Device Server for Distributed Control, by Gerkey et al, 2001.