CS686: CS686: Motion Planning and Applications Sung-Eui Yoon ( 윤성의 ) ( 윤성의 ) C Course URL: URL http://sglab.kaist.ac.kr/~sungeui/MPA
About the Instructor About the Instructor ● Joined KAI ST at 2007 Joined KAI ST at 2007 ● B.S., M.S. at Seoul National Univ. ● Ph.D. at Univ. of North Carolina-Chapel Hill ● Post. doc at Lawrence Livermore Nat’l Lab ● Main research focus ● Handling of massive data for various computer g p graphics and geometric problems 2
My Recent Work My Recent Work 3
Welcome to CS780 Welcome to CS780 I nstructor: Sung-eui Yoon Email: sungeui@gmail.com Office: 3432 at CS building Class time: 4:00pm – 5:15pm on T/ Th Class location: 3444 in the CS building Class location: 3444 in the CS building Office hours: 3:00–4:00 MWF (or by appt.) Course webpage: Course webpage: http:/ / sglab.kaist.ac.kr/ ~ sungeui/ MPA TA: TA: Duksu Kim (XXX) Duksu Kim (XXX) 4
Real World Robots Real World Robots Sony Aibo Sony Aibo ASIMO ASIMO Courtesy of Prof. Dinesh Manocha 5 Da Vinci
Motion of Real Robots Motion of Real Robots Humanoid Robot: Humanoid Robot: http://youtube.com/watch?v=NYoY4p0_yaI&mode=related&search= 6
Motion of Real Robots Motion of Real Robots Humanoid Robot: Humanoid Robot: http://www.youtube.com/watch?v=ZkYQWBXpk_0 7
Motion of Real Robots Motion of Real Robots Autonomous robot Autonomous robot http://www.youtube.com/watch?v=3SQiow-X3ko 8
Motion of Real Robots Motion of Real Robots Medical robot: Medical robot: http://www.youtube.com/watch?v=XfH8phFm2VY 9
Open Platform Humanoid Project: DARwIn OP Project: DARwIn-OP Just USD 8K! http://www.youtube.com/watch?v=0FFBZ6M0nKw 10
Motion of Virtual Worlds Motion of Virtual Worlds 11
Motion of Virtual Worlds Motion of Virtual Worlds Computer generated simulations: Computer generated simulations: http://www.youtube.com/watch?v=5-UQmVjFdqs 12
Motion of Virtual Worlds Motion of Virtual Worlds Computer generated simulations games virtual prototyping: Computer generated simulations, games, virtual prototyping: http://www.massivesoftware.com/ 13
Smart Robots or Agents Smart Robots or Agents ● Autonomous agents that sense, plan, and Autonomous agents that sense plan and act in real and/ or virtual worlds ● Algorithms and systems for representing ● Algorithms and systems for representing, capturing, planning, controlling, and rendering motions of physical objects g p y j ● Applications: ● Applications: ● Manufacturing ● Mobile robots ● Computational biology ● Computer-assisted surgery ● Digital actors 14
Goal of Motion Planning Goal of Motion Planning ● Compute motion strategies, e.g.: Compute motion strategies e g : ● Geometric paths ● Time parameterized trajectories ● Time-parameterized trajectories ● Sequence of sensor-based motion commands ● Aesthetic constraints ● Aesthetic constraints ● Achieve high-level goals, e.g.: ● Achieve high level goals, e.g.: ● Go to A without colliding with obstacles ● Assemble product P p ● Build map of environment E ● Find object O 15
Basic Motion Planning Problem Basic Motion Planning Problem ● Statement: Statement: ● Compute a collision-free path for an object (the robot) among obstacles subject to robot) among obstacles subject to CONSTRAI NTS ● I nputs: I nputs: ● Geometry of robot and obstacles ● Kinematics of robot (degrees of freedom) ( g ) ● I nitial and goal robot configurations (placements) ● Outputs: ● Continuous sequence of collision-free robot configurations connecting the initial and goal fi ti ti th i iti l d l configurations 16
Examples with Rigid Object Examples with Rigid Object Ladder problem Piano-mover problem 17
Is It Easy? Is It Easy? 18
Example with Articulated Object Example with Articulated Object 19
Some Extensions of Basic Problem Problem ● Multiple robots ● Optimal planning M lti l b t O ti l l i ● Assembly planning ● Uncertainty in model, control and sensing control and sensing ● Acquire information by A i i f ti b ● Exploiting task sensing mechanics (sensorless ( ● Model building Model building motions, under- ● Object finding/ tracking actualted systems) ● I nspection ● Physical models and Ph i l d l d ● Nonholonomic deformable objects constraints ● I ntegration of planning ● I ntegration of planning ● Dynamic constraints and control ● Stability constraints ● I ntegration with I ntegration with higher-level planning 20
Examples of Applications Examples of Applications ● Manufacturing: ● Graphic animation of M f t i G hi i ti f “digital actors” for ● Robot programming video games, movies, g , , ● Robot placement ● Robot placement and webpages ● Design of part feeders ● Virtual walkthrough ● Design for Design for ● Medical surgery manufacturing and planning servicing ● Generation of plausible ● Design of pipe layouts G ti f l ibl i f i l molecule motions, e.g., and cable harnesses docking and folding g g ● Autonomous mobile ● Autonomous mobile motions robots planetary ● Building code exploration, verification ifi ti surveillance, military ill ili scouting 21
Assembly Planning and Design of Assembly Planning and Design of y Manufacturing Systems Manufacturing Systems
Application: Checking Building Code Application: Checking Building Code Application: Checking Building Code Application: Checking Building Code
Cable Harness/ Pipe design Cable Harness/ Pipe design Cable Harness/ Pipe design Cable Harness/ Pipe design
Humanoid Robot Humanoid Robot Humanoid Robot Humanoid Robot [Kuffner and Inoue, 2000] (U. Tokyo)
Digital Actors Digital Actors g A Bug’s Life (Pixar/Disney) Toy Story (Pixar/Disney) Antz (Dreamworks) Tomb Raider 3 (Eidos Interactive) The Legend of Zelda (Nintendo) Final Fantasy VIII (SquareOne)
Motion Planning for Digital Actors Motion Planning for Digital Actors Motion Planning for Digital Actors Motion Planning for Digital Actors Manipulation Sensory-based locomotion
Application: Computer Application: Computer Assisted Surgical Planning Application: Computer Application: Computer-Assisted Surgical Planning Assisted Surgical Planning Assisted Surgical Planning
Radiosurgical Planning Radiosurgical Planning Radiosurgical Planning Radiosurgical Planning Cyberknife Cyberknife
Study of the Motion of Bio Study of the Motion of Bio-Molecules Study of the Motion of Bio Study of the Motion of Bio-Molecules Molecules Molecules • Protein folding • Ligand binding • Ligand binding
DARPA G DARPA Grand Challenge d Ch ll Planning for a collision free 132 mile path Planning for a collision-free 132 mile path in a desert The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL
Prerequisites Prerequisites ● Basic knowledge of probability B i k l d f b bilit ● E.g., events, expected values, etc ● I f you are not sure, please consult the instructor at the end of the course instructor at the end of the course 32
Topics Topics ● Underlying geometric concepts of motion Unde l ing geomet ic concepts of motion planning ● Configuration space ● Configuration space ● Motion planning algorithms: ● Complete motion planning ● Complete motion planning ● Randomized approaches ● Kinodynamic constraints ● Kinodynamic constraints ● Character motion in virtual environments ● Multi agent and crowd simulation ● Multi-agent and crowd simulation The course is about motion planning The course is about motion planning algorithms, not control of real robots! 33
Course Overview Course Overview ● 1/ 2 of lectures and 1/ 2 of student 1/ 2 of lectures and 1/ 2 of student presentations ● This is a research-oriented course ● This is a research-oriented course ● Paper reading list ● What you will do: ● Choose papers that are interesting to you Choose papers that are interesting to you ● Present those papers ● Propose ideas that can improve the state-of- p p the-art techniques; implementation is not required, but is recommended ● Quiz and mid-term Quiz and mid term ● and, have fun! 34
Presentations and Final Project Presentations and Final Project ● For each paper: For each paper: ● Consider its main idea given its context ● Look at pros and cons of each method ● Look at pros and cons of each method ● Think about how we can efficiently handle more realistic and complex scene more realistic and complex scene ● Propose ideas to address those problems ● Show convincing reasons why your ideas can Show convincing reasons why your ideas can improve those problems ● I mplementation is optional 35
Course Awards Course Awards ● Best speaker and best project Best speaker and best project ● For the best presenter, a small research related device will be supported ● For the best project, a high grade will be given given 36
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