non-gaited humanoid locomotion planning

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Non-Gaited Humanoid Locomotion Planning. Kris Hauser, Tim Bretl, and Jean-Claude Latombe Stanford University. What are humanoids capable of?. What are humanoids capable of?. What are humanoids capable of?. What are humanoids capable of?. Mom!. Navigating Difficult Terrain. - PowerPoint PPT Presentation

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Non-Gaited Humanoid Locomotion Planning

Kris Hauser, Tim Bretl, and Jean-Claude Latombe

Stanford University

Non-Gaited Humanoid Locomotion Planning Kris Hauser

What are humanoids capable of?

Non-Gaited Humanoid Locomotion Planning Kris Hauser

What are humanoids capable of?

Non-Gaited Humanoid Locomotion Planning Kris Hauser

What are humanoids capable of?

Non-Gaited Humanoid Locomotion Planning Kris Hauser

What are humanoids capable of?

Mom!

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Navigating Difficult Terrain Each step different from previous! Very uneven Friction Contacts with hands, knees, etc. Obstacles

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Previous Work “Footstep-search” planners

Set of candidate next-step moves How many are needed? What if you need more?

Non-Gaited Humanoid Locomotion Planning Kris Hauser

LEMUR II Robot Free-climbing robot on vertical terrain Extend technique to HRP-2

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Non-Gaited Planning Do not require predefined motions Single-step motions created automatically

with Probabilistic Roadmap planner Arbitrary-geometry robots Arbitrary-geometry terrain Any part of the body allowed for contact

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Applications Autonomous navigation

More than just rough terrain! Motion library generation Robot design

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Non-Gaited Planner Multi-Step Planning: Search for a sequence

of steps that is likely to be feasible

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Single StepStance A Stance BTransition

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Single Step Feasible SpaceStance A Stance BTransition

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Single Step Feasible SpaceStance A Stance BTransition

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Non-Gaited Planner Multi-Step Planning: Search for a sequence

of steps that is likely to be feasible Random sampling

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Non-Gaited Planner Multi-Step Planning : Search for a sequence

of steps that is likely to be feasible Random sampling

Sample feasible configurations faster Iterative Constraint Enforcement (ICE)

Non-Gaited Humanoid Locomotion Planning Kris Hauser

ICE Sampling Demo

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Non-Gaited Planner Multi-Step Planning: Search for a sequence

of steps that is likely to be feasible Random sampling

Single-Step Planning: Plan a quasi-static motion along these steps Probabilistic roadmap planner

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Planned Motions – Noise Terrain 400 random

candidate foot contacts

1.5 hr multi-step 10 min single-step

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Planned Motions – Noise Terrain 2 800 random

candidate foot/hand contacts

3 hr multi-step 3 min single-step

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Planned Motions – Steps 0.4 m: 0.5 m: must use hands!

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Planned Motions - Ladder 45 manually placed

candidate contacts 7 min multi-step 3 hr single-step

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Future work Determine infeasible steps quickly Choice of candidate steps Smoothness, safety, efficiency of paths Experiment with physical HRP-2

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Questions?

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Feasible Space Sampling Contact Equilibrium Collision-free

Contacts

q1

qn

q2

q3

Contact Submanifold

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Feasible Space Sampling Contact Equilibrium Collision-free

Support Polygonqn

q2

q3

Equilibrium constraint

Center of Mass

q1

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Feasible Space Sampling Contact Equilibrium Collision-free

qn

q2

q3

Equilibrium constraint

q1

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Feasible Space Sampling Contact Equilibrium Collision-free

Obstacle

qn

q2

q3

q1

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Feasible Space Sampling Contact Equilibrium Collision-free

qn

q2

q3

q1

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Feasible Space Sampling Contact Equilibrium Collision-free

qn

q2

q3

q1

Rejection rate is high!

(often > 99.9%)

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Iterative Constraint Enforcement Numerical,

iterative IK solver Solves contact

constraints

q1

q2

q3

Non-Gaited Humanoid Locomotion Planning Kris Hauser

Iterative Constraint Enforcement Numerical,

iterative IK solver Solves contact

constraints ICE: Incorporate

equilibrium and collision constraints too q1

q2

q3

Non-Gaited Humanoid Locomotion Planning Kris Hauser

ICE vs. Direct Parameterization Transition from 1 2 feet, flat ground

Non-Gaited Humanoid Locomotion Planning Kris Hauser

ICE vs. Direct Parameterization Transition from 1 2 feet, flat ground

DP ICE

ms / sample 0.83 69

% successful 0.02 26

ms / successful 4,150 265

Non-Gaited Humanoid Locomotion Planning Kris Hauser

ICE vs. Direct Parameterization Transition from 1 2 feet, flat ground

DP ICE

ms / sample 0.83 69

% successful 0.02 26

ms / successful 4,150 265

Non-Gaited Humanoid Locomotion Planning Kris Hauser

ICE vs. Direct Parameterization Transition from 1 2 feet, flat ground

DP ICE

ms / sample 0.83 69

% successful 0.02 26

ms / successful 4,150 265

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