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Motion Algorithms: Motion Algorithms: Planning, Simulating, Analyzing Planning, Simulating, Analyzing Motion of Physical Objects Motion of Physical Objects Jean-Claude Latombe Computer Science Department Stanford University
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Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Mar 21, 2016

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Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects. Jean-Claude Latombe Computer Science Department Stanford University. Pernes-les-Fontaines. About Myself. Born a long time ago in South-East of France. About Myself. Born a long time ago in South-East of France - PowerPoint PPT Presentation
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Page 1: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Motion Algorithms:Motion Algorithms:Planning, Simulating, Analyzing Planning, Simulating, Analyzing

Motion of Physical ObjectsMotion of Physical Objects

Jean-Claude Latombe

Computer Science DepartmentStanford University

Page 2: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

About Myself Born a long time ago in South-East of

France

Pernes-les-Fontaines

Page 3: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

About MyselfAbout Myself Born a long time ago in South-East of

France Studied in Grenoble

(Eng. EE, MS EE, PhD CS 1977)

CS Professor, Grenoble (1980-84)

CEO, ITMI (1984-87) Stanford (1987-…)

Page 4: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Research InterestsResearch Interests 1980-84: Artificial Intelligence,

Computer Vision, Robotics 1987-92: Robot Motion Planning 1993-98: Motion Planning 1998-…: Motion Algorithms

Page 5: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects
Page 6: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Fundamental QuestionFundamental QuestionAre two given points connected by a path?

Page 7: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

How Do You Get There?How Do You Get There?

?

Page 8: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

How Do You Get There?How Do You Get There?

Problems:• Geometric complexity• Space dimensionality

Page 9: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Increasing ComplexityIncreasing Complexity

Page 10: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

New ProblemsNew ProblemsAssembly planning

Target finding

Page 11: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

From Simulation to Real RobotsFrom Simulation to Real Robots

Page 12: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Space RobotsSpace Robots

air bearing

gas tankair thrusters

obstacles

robot

Page 13: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Modular Reconfigurable Modular Reconfigurable RobotsRobots

Xerox, ParcXerox, Parc

Casal and Yim, 1999

Page 14: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects
Page 15: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Humanoid RobotHumanoid Robot[Kuffner and Inoue, 2000] (U. Tokyo)

Stability constraints

Page 16: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

RadiosurgeryRadiosurgery

Page 17: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

From Robots to Other Agents: From Robots to Other Agents: Digital ActorsDigital Actors

Page 18: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Simulation of Deformable Simulation of Deformable ObjectsObjects

Page 19: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Study of Molecular MotionStudy of Molecular Motion

Ligand bindingProtein folding

Page 20: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Basic Tool: Configuration SpaceBasic Tool: Configuration Space

Approximate the free space by random sampling

Probabilistic Roadmaps

[Lozano-Perez, 80]

Page 21: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Probabilistic Roadmap (PRM)Probabilistic Roadmap (PRM)

free space

Page 22: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Probabilistic Roadmap (PRM)Probabilistic Roadmap (PRM)

free space

mmbb

mmgg

milestone

local path

Page 23: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

First Assumption of PRM First Assumption of PRM PlanningPlanning

Collision tests can be done efficiently.

[Quinlan, 94; Gottschalk, Lin, Manocha, 96]

Several thousand collision checks per second for 2 objects of 500,000 triangles each on a 1-GHz PC

Page 24: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

ProblemProblem

Page 25: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Exact Collision Checking Exact Collision Checking of Path Segmentsof Path Segments

• Idea: Use distance computation in workspace rather than pure collision checking D = 2Lx|dq1|+L|dq2|

3Lxmax{|dq1|,|dq2|}d

q1

q2

If D d then no collision

Page 26: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Exact Collision Checker in Exact Collision Checker in ActionAction

Page 27: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Second Assumption of PRM Second Assumption of PRM PlanningPlanning

A relatively small number of milestones and local paths are sufficient to capture the connectivity of the free space.

Page 28: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Probabilistic CompletenessProbabilistic CompletenessIn an expansive space, the probability that

a PRM planner fails to find a path when one exists goes to 0 exponentially in the number of milestones (~ running time).

Page 29: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Narrow-Passage IssueNarrow-Passage Issue

Page 30: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Application to BiologyApplication to Biology

vi

vj

Pij

otherwise. ,1

;0 if ,)/exp(

i

iji

Bij

ij

N

EN

TkE

P

Markov chain + first-step analysis ensemble properties

Page 31: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Current ProjectsCurrent ProjectsRobot motion planningFunding: General Motors, ABBCollaborator: Prinz (ME), Rock (AA)Study of molecular motions (folding, binding)Funding: NSF-ITR (with Duke and UNC), BioXCollaborators: Guibas (CS), Brutlag (Biochemistry), Levitt (Structural Biology), Pande (Chemistry), Lee (Cellular B.)Surgical simulation (deformable tissue, suturing, visual and haptic feedback)Funding: NSF, NIH, BioXCollaborators: Salisbury (CS+Surgery), Girod (Surgery), Krummel (Surgery)Modeling and simulation of deformable objectsFunding: NSF-ITR (with UPenn and Rice)Collaborators: Guibas (CS), Fedkiw (CS)

Page 32: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Pakistan Afghanistan Tadjikistan

Cho-Oyu, 8200m, ~27,000ft (Tibet)

Muztagh Ata, 7,600m, 25,000ft (Xinjiang, China)

Third Pillar of Dana(California)

Thailand

Page 33: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Rock-Climbing RobotRock-Climbing Robot

With Tim Bretl and Prof. Steve Rock

Page 34: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects

Half-Dome, NW Face, Summer of 2010 …

Tim Bretl

Page 35: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects
Page 36: Motion Algorithms: Planning, Simulating, Analyzing Motion of Physical Objects