Algorithms for Sensor-Based Robotics: Introduction and Background Computer Science 436/636 https://cirl.lcsr.jhu.edu/sensorbasedrobotics/ Greg Hager Simon Leonard With slides borrowed from Zach Dodds and Howie Choset
What is a Robot? Autonomous, automaton self-willed (Greek, auto+matos) Robot Czech writer Karel Capek in 1923 play R.U.R. (Rossum s Universal Robots) labor (Slovak or Polish, robota) workman (Slovak or Polish, robotnik) In the play, robots take over the world!
Haptics Robotics from 50,000 feet Task level planning Mapping and Localization HRI Dynamics and Control (ME 646) Mechanisms Motion Planning Vision Manipulation 2/7/14 Applications CS 436/636, G.D. Hager
Two Key Problems 1. Motion Planning: Given a mechanism, a known environment, and a known start and goal, compute a set of inputs (e.g. a joint trajectory) that moves the robot from start to goal without collision. 2. Localization and Mapping: Given no a priori knowledge, use information from sensing and motion to simultaneously compute a model of the environment (a map) and robot location within the environment.
What is Motion Planning? Determining where to go...more than a search (or it is a geometric search) 2/7/14 CS 436/636, G.D. Hager
Basic Path Planning Problem Statement: Compute a continuous sequence of collision-free robot configurations connecting the initial and goal configurations 2D EXAMPLE: Geometry of environment Geometry and kinematics of robot Initial and goal configurations 2/7/14 Path Planner CS 436/636, G.D. Hager Collision-free path
Live Motion Planning Experiments Person 1 walks through some obstacles Person 1, looking at Person 2, directs Person 2 through obstacles Person 1, looking at Person 2 with eyes closed, directs Person 2 through obstacles Person 1, looking at a map and not Person 2, whose eyes are still closed, directs Person 2 through obstacles Person 1, looking at an object and Person 2, whose eyes are closed, directs Person 2 to grab an obstacle How do we do the last experiment with a map? 2/7/14 CS 436/636, G.D. Hager
What did we assume? Perfect sensors? What information Uncertainty Perfect control? What controls? What else? Uncertainty Perfect thinking? Knowledge of the world? Complete? Processing the world? Everything? 2/7/14 CS 436/636, G.D. Hager
Probabilistic Methods/Drug Design Courtesy Lydia Kavraki et al.
RoadMap Methods/Animation Path planning in high dimensional spaces Kuffner/Latombe/LaValle
Think About Dynamics, Too! Visually controlled juggling 3R manipulator 3-5 full frames / bounce used half-frames Al Rizzi, Noah Cowan, Rob Burridge, & Dan Koditschek estimated single-frame motion obstacle avoidance?!
Vision-Based Juggling
Planning in Juggling Space
SLAM Suppose you wake up in the desert and you need to find your way around --- how do you do it? A Chicken and Egg problem?
This Course: We will focus on two robotics problems: Robot Motion Planning: How do I get from A to B in an environment Robot Localization and Mapping: What is the structure of space, and where am I in it. We will primarily focus on algorithms, their analysis, and their implementation (when possible) from real sensor data We will focus on the *static* planning problem the world does not change our own momentum does not matter Almost all of our work will be in simulation although if you take Robocup I/II, you will be able to apply it to real robots
Book http://motionplanning.com Principles of Robot Motion: Theory, Algorithms, and Implementations H. Choset, K. M. Lynch, S. Hutchinson, G. Kantor, W. Burgard, L. E. Kavraki and S. Thrun, MIT Press, Boston, 2005. 2/7/14 CS 436/636, G.D. Hager
Other Books Planning Algorithms Steven Lavalle, Cambridge University Prress, 2006 Robot Motion Planning, Jean-Claude Latombe, Kluwer, 1991. Free download: http://planning.cs.uiuc.edu/ Probabilistic Robotics S. Thrun, W. Burgard, D. Fox MIT Press, 2006 An Introduction to AI/Robotics Robin Murphy MIT Press, 2006 2/7/14 CS 436/636, G.D. Hager
This Course: Text: Principles of Robot Motion: Theory, Algorithms, and Implementation, Choset et. al, 2005 Chap 1: Introduction Chap 3: Kinematics and Configuration Space Chap 4: Potential Field Methods Chap 5: Roadmaps EXAM Chap 6: Cell decompositions Chap 7: Sampling-Based Motion Planning Chap 8: Kalman-Filter based Localization Chap 9: Bayesian Methods for Localization EXAM
Homework Assignments HW 1: Kinematics design HW 2: Simulation HW 3: Probabilistic Roadmap HW 4: SLAM Possibly a final project 2/7/14 CS 436/636, G.D. Hager
MoveIt! MoveIt! is a software for mobile manipulation, incorporating the latest advances in motion planning, manipulation, 3D perception, kinematics, control and navigation. http://moveit.ros.org/
General Policies Homework: Roughly 4 assignments (about every 2 weeks) counts for 50% of grade. Exams count the other 50% I expect everyone to come to every lecture I welcome feedback as we go along (I m learning too!)
Chapter 1 The Piano-movers problem: Schwarz & Sharir ~ 1980 --- spawned a series of papers on rigid objects moving in space Early work theory based --- Canny PhD 1988 --- planning is Pspacehard! Lozano-Perez (Mason & Taylor) -- notions of configuration space and effective algorithms in the plane (1987) Latombe (early 90 s) -- efficient approximate methods Kavraki (and others, mid/late 90 s) probabilistic methods Now, considered by many to be a solved problem for typical serial chain robots Still some open problems for non-holonomic systems (e.g. a double-semi backing up) and complex dynamics (multiple airliners in turbulance)
Robotics is 50! First commercial robot by Unimate sold in 1961 2/7/14 CS 436/636, G.D. Hager
A Brief Pre-History 270 BC: Clocks with movable figures 1495: da Vinci designs mechanical man 1801: Jacquard programmable loom 1921: Capek s RUR 1940: The tortoise 1954: Devol creates first programmable robot 1960: JHU The Beast 2/7/14 CS 436/636, G.D. Hager
Classical / Hierarchical Paradigm Sense Plan Act 70s Focus on automated reasoning and knowledge representation STRIPS (Stanford Research Institute Problem Solver): Perfect world model, closed world assumption Find boxes and move them to designated position
Shakey 69 Stanford Research Institute
Stanford CART 1973 1961 Stanford Artificial Intelligence Laboratory / CMU (Moravec)
Stanford CART Stanford Artificial Intelligence Laboratory / CMU (Moravec)
Historical Search-based AI Shakey the Robot (SRI, 1966 1972) Triangulating range-finder for sensing obstacles STRIPS based A* planner for navigating to a goal Wireless radio and video camera What have we done since? 2/7/14 CS 436/636, G.D. Hager
Blocks World (1960s) Historical Search-based AI 2/7/14 CS 436/636, G.D. Hager
Historical Search-based AI STRIPS Action Planning (1960s) 2/7/14 CS 436/636, G.D. Hager
Historical Search-based AI STRIPS Action Planning (1960s) 2/7/14 CS 436/636, G.D. Hager
Reactive / Behavior-based Paradigm Sense Act No models: The world is its own, best model Easy successes, but also limitations Investigate biological systems
Reactive Robots Genghis, Rodney Brooks
Polly (Horswill, 1992) The Polly System: specializing perception to a single task/environment a vision-based tour guide at MIT: Polly tested the limits of reactivity.
Hybrid Deliberative/reactive Paradigm Plan Sense Act Combines advantages of previous paradigms World model used for planning Closed loop, reactive control
Trends in Robotics Research Classical Robotics (mid-70 s) exact models no sensing necessary Hybrids (since 90 s) model-based at higher levels reactive at lower levels Reactive Paradigm (mid-80 s) no models relies heavily on good sensing Probabilistic Robotics (since mid-90 s) seamless integration of models and sensing inaccurate models, inaccurate sensors
Robotics Today 2/7/14 CS 436/636, G.D. Hager
Incredible Pla-orms for Research Lots of Bodies 1.1. STATE OF THE ART Willow Garage PR2 3 NASA Robonaut Rethink RoboHcs DLR JusHn Willow Garage PR2 Figure 1.1: DLR s Justin (www.dlr.de) CS 436/636, G.D. Hager Figure 1.2: Willow Garage s PR2 (www.willowgarage.com)
Robots in Space Opportunity & Spirit on Mars since Jan. 04
In the Air By 2020, all aircraft bought by the military will be unmanned
Land and Sea... RHex: Koditschek, Rizzi, Cowan,...
A New Record hlp://www.youtube.com/watch?v=zamdgoskura CS 436/636, G.D. Hager
Snake Robots Inspection or Search (courtesy Howie Choset)
Scalable robot for dexterous surgery in small spaces Nabil Simaan, Russell Taylor, Paul Flint, MD 4.2 mm diameter >1 N force application ability -- Impedance control master and slave manipulator -- Remote wrist for high dexterity -- Stereo endoscopic visualization
Applications: Medicine Courtesy Peter Kazanzides -- Integrated Surgical Systems, Inc
Intuitive Surgical da Vinci System K v Master Position Slave Position -- Impedance control master and slave manipulator -- Remote wrist for high dexterity -- Stereo endoscopic visualization
Heart Lander Riviere/Patronik/Zenati (CMU/U. Pittsburgh) Subxiphoid approach attach to beating heart via suction maneuver to site perform therapy Working Channel A new concept for minimally invasive surgery!
How Do Robots Today Make a Living? Courtesy KUKA RoboHcs Courtesy of IntuiHve Surgical ROOMBA, Courtesy IRobot KIVA Systems CS 436/636, G.D. Hager
Humanoids (DARPA Robotics Challenge) CMU Tartan 2/7/14 NASA Valkyrie CS 436/636, G.D. Hager
Minerva: A Museum Tour Guide CMU/University of Bonn
Your Assignment3 Read chapter 3 for the next class!