Collision in Human Robot Collaboration Fabrizio Flacco - - PowerPoint PPT Presentation

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Collision in Human Robot Collaboration Fabrizio Flacco - - PowerPoint PPT Presentation

Collision in Human Robot Collaboration Fabrizio Flacco Dipartimento di Ingegneria Informatica, Automatica e Gestionale AMR Prof. G. Oriolo Safe pHRI Human friendly robots Safety Coexistence Collaboration Rome, April 17 2012 pHR


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Collision in Human Robot Collaboration

Fabrizio Flacco

Dipartimento di Ingegneria Informatica, Automatica e Gestionale AMR – Prof. G. Oriolo

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Rome, April 17 2012 pHR Cooperation @ AMR 2

Safe pHRI

Human friendly robots

Collaboration Coexistence Safety

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Rome, April 17 2012 pHR Cooperation @ AMR 3

Coexistence

YESTERDAY

1989

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Rome, April 17 2012 pHR Cooperation @ AMR 4

Coexistence

TODAY

2012

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Coexistence

TOMORROW

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Rome, April 17 2012 pHR Cooperation @ AMR 6

Safety

Top-down hierarchy

Collision avoidance Physical collision detection Variable Stiffness Actuator Lightweight and compliant robots

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Rome, April 17 2012 pHR Cooperation @ AMR 7

Depth sensors

From stereovision to the Kinect

Stereovision Time of Flight Structured Light

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Rome, April 17 2012 pHR Cooperation @ AMR 8

Depth space

A 2.5 dimensional space

Non-homogeneous 2.5 dimensional space

  • x,y position of the point in the image plane (pixel)
  • d depth of the point w.r.t. the image plane (m)

The depth space is modeled as a pin-hole Point in a Cartesian reference frame Point in the sensor frame Point in the depth space

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Rome, April 17 2012 pHR Cooperation @ AMR 9

Depth Image

How to use it?

Configuration Space Cartesian Space Depth Space

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Configuration Space

Only for few dof

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Rome, April 17 2012 pHR Cooperation @ AMR 11

Cartesian Space

A long process

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Rome, April 17 2012 pHR Cooperation @ AMR 12

Depth Space

Distance Evaluation

Distance between a point of interest and an obstacle point

do>dp yes no

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Rome, April 17 2012 pHR Cooperation @ AMR 13

Robot Depth Image

All known

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Rome, April 17 2012 pHR Cooperation @ AMR 14

Repulsive Vector

A potential field like method

Repulsive vector generated from the distance vector Repulsive vector due to a single obstacle point The repulsive vectors due to all obstacles near to the point of interest are considered.

  • orientation -> sum of all

repulsive vectors

  • magnitude -> nearest
  • bstacle
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Rome, April 17 2012 pHR Cooperation @ AMR 15

Repulsive Vector

A potential field like method

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Repulsive Vector

A potential field like method

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Rome, April 17 2012 pHR Cooperation @ AMR 17

Case of obstacles faster than control point Obstacles velocity taken into account by considering the variation of the repulsive vector O PoI O PoI

Obstacle Velocity

The pivot method

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Rome, April 17 2012 pHR Cooperation @ AMR 18

  • End effector

repulsive vector repulsive velocity

  • Collision avoidance for the robot body
  • Fluid, jerk limited motions feeling of safety

www.reflexxes.com

Repulsive vector Cartesian Constrains Joint velocity limit

Motion Control

End effector and other control points

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Rome, April 17 2012 pHR Cooperation @ AMR 19

Safe Coexistence

Collision avoidance in depth space

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Rome, April 17 2012 pHR Cooperation @ AMR 20

Collaboration

Physical and contactless

In physical collaboration, there is an explicit and intentional contact with exchange of forces between human and robot. By measuring or estimating these forces, the robot can predict human motion intentions and react accordingly. In contactless collaboration, there is no physical interaction: coordinated actions are guided or follow from an exchange of information, which can be achieved via direct commu- nication, like with gestures and/or voice commands, or indirect communication, by recognizing intentions or attention, e.g., through eye gaze.

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Safe Physical Collaboration

Allow contacts

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From human body to gesture recognition

Contactless Collaboration

Voice and Gesture

Speech recognition

Start Collaboration Starting Collaboration

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Contactless Collaboration

Voice and Gesture

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Contactless Collaboration

Voice and Gesture

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Collision in Human Robot Collaboration

Fabrizio Flacco

Dipartimento di Ingegneria Informatica, Automatica e Gestionale AMR – Prof. G. Oriolo