grasp lab - ros.orgplanning for autonomous opening of spring-loaded doors maxim likhachev...

University of PennsylvaniaGRASP LAB

PR2GRASP:

From Perception and Reasoningto Grasping

Led by Maxim Likhachev

Kostas Daniilides Vijay Kumar

Katherine J. Kuchenbecker Jianbo Shi

Daniel D. Lee Camillo Jose Taylor

Mark Yim

Student Representatives:Mike Phillips

Benjamin CohenCody Phillips

Soonkyum Kim

@ GRASP Lab

Research Proposal

● Planning for Navigation in Dynamic Environments– Maxim Likhachev

● Pennochio Project to Establish Telepresence through PR2– CJ Taylor & Mark Yim

● Support for Modular End Effectors on PR2– Mark Yim

● Planning for Autonomous Opening of Spring-Loaded Doors– Maxim Likhachev

● Transferring Natural Handheld Objects between PR2 and Human and other Robots – Katherine Kuchenbecker & Maxim Likhachev

● Tracking People in Cluttered Spaces for Navigation in Dynamic Environment – Jianbo Shi & Maxim Likhachev

● Visual Localization and Pose Estimation of Objects for Grasping– Kostas Daniilides

● Planning and Controls for two-arm Manipulation– Vijay Kumar & Maxim Likhachev

● Learning salient features for better perceptual processing by PR2 – Dan Lee

Planning for Autonomous Opening of Spring-Loaded DoorsMaxim Likhachev

Motivation:● Spring loaded doors are all around us!● So the PR2 can use fire exits in case of an emergency

● Help save old people & children● Save Itself

Goal:● A principled approach to:

● plan a complete motion to open a spring loaded door● using the arm(s) and base of the robot● collision-free trajectory for the complete robot body● can be used on any door or cabinet● provides completeness & suboptimality guarantees

Planning for Autonomous Opening of Spring-Loaded DoorsBenjamin Cohen, Maxim Likhachev

Planning for Autonomous Door Opening with a Mobile ManipulatorSachin Chitta, Benjamin Cohen, Maxim Likhachev

ICRA 2010

Transferring Natural Handheld Objects between PR2 and Human and other RobotsJoe Romano, Katherine Kuchenbecker

● In order to move robots into the home they need to interact naturally with people.

● Passing objects to a human, and receiving objects passed from a human, constitute a basic but important robot skill.

● It is important to follow social conventions:● passing at the right speed● passing or accepting when the human is ready

● ...without violating the mechanical constraints of the interaction:

● letting go when the human is ready● applying and releasing stable grasps

● We plan to use tactile cues, such as contact acceleration signals, to detect important events in the interaction.

Pennochio Project to Establish Telepresence through PR2CJ Taylor, Mark Yim

● Explore using the PR2 for immersive teleoperation

– Leverage inexpensive Head Mounted Displays– Slave Pan Tilt head to real-time motion capture– Map motion of user onto motion of base and arms– Develop hand held manipulative units to control motion of the grippers and to provide haptic

feedback– Archive motion and sensor data for use in teaching by example systems– Explore use of low cost Markerless Motion capture

● Some Related Projects:

– MARIONET – UT Austin– Interaction Lab - USC

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Support for Modular End Effectors on PR2Mark Yim

Goal:● Change end effectors to suit tasks

Issues:● What types of end effectors would be useful?● Gravity compensation in arm requires same moment/mass

from end-effector● Low level software requires modification to handle change

in hardware state● High level ROS PR2 interface needs to support end-

effector types

Support for Modular End Effectors on PR2Mark Yim

Planning for Navigation in Dynamic EnvironmentsMike Phillips, Maxim Likhachev

Motivation● Dynamic Obstacles are all around us!● Household tasks require navigation around people and pets

ProblemGiven:

● Map of the static environment● Pose of the robot and goal● Predicted trajectories of dynamic obstacles

Output:● A time parameterized path that gets the robot safely to the goal

A common approach is to treat dynamic obstacles as static and replan often

– This is fast but lacks optimality and completeness

Another approach adds a time dimension to the search space

– Is optimal and complete but very slow due to increased dimensionality

Our approach exploits the idea that dynamic obstacles generally occupy a small fraction of the environment

– We build planners that only use a time dimension when relevant

• Most of the space is free of dynamic obstacles

– This allows for fast planning times while still guaranteeing optimality and completeness


Time-bounded lattice for efficient planning in dynamic environmentAleksandr Kushleyev, Maxim Likhachev

ICRA 2009


• This planner will be run on the PR2

• Planning times are all < 1 sec


Tracking People in Cluttered Spaces for Navigation in Dynamic Environment Jianbo Shi, Maxim Likhachev

People are all around us!

Household tasks require robots to identify and track people

Tracking people can become more robust to occlusion if planning is used to predict trajectories people may follow

Tracking People in Cluttered Spaces for Navigation in Dynamic EnvironmentJianbo Shi, Maxim Likhachev

● Object recognition/Localization● 3D pose estimation● Most approaches texture-based

– Exists “problem objects”– Glasses, bottles, cups– Shiny, transparent objects

● Shape-based approach– Recognize by shape– Learn from 3D model library

Visual Localization and Pose Estimation of Objects for GraspingCody Phillips, Alex Toshev, Kostas Daniilidis

Grasping By Shape (Single Image)● Extract 2D views from 3D models● Compute shape descriptors● Hypothesize object and pose

Shapes Match?

Recover Pose!


Grasping By Shape (Video)● Multiple object camera views● Combine evidence from views● Refine hypothesis space

HypothesesGeometricallyConsistent


Planning & Controls for two-arm ManipulationSoonkyum Kim, Vijay Kumar, Maxim Likhachev

Goal:● Perform manipulation tasks that require two arm

coordination

Challenges:● Maintain and control contacts between object and

end effector● Maintain force closure● Rolling/sliding could occur● Redundant system

Cooperative Quasi-Static Planar Manipulation with Multiple Robots. Quentin J. Lindsey, Michael Shomin, and Vijay Kumar.

IDETC 2010


A general paradigm for control:● Control for trajectory + control for contact● Nonlinear feedback controller

Planning:● Partition of the configuration space● Construct compact graph● Search-based planning


Thank You!

grasp lab - ros.orgplanning for autonomous opening of spring-loaded doors maxim likhachev...

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