Research Papers

On Superquadric Human Modeling and Risk Assessment for Safe Planning of Human-Safe Robotic Systems

[+] Author and Article Information
Nima Najmaei

Department of Electrical and Computer Engineering, University of Western Ontario, London, ON N6A 3K7, Canadannajmaei@uwo.ca

Mehrdad R. Kermani

Department of Electrical and Computer Engineering, University of Western Ontario, London, ON N6A 3K7, Canadamkermani@eng.uwo.ca

J. Mechanisms Robotics 2(4), 041008 (Sep 30, 2010) (9 pages) doi:10.1115/1.4002345 History: Received March 02, 2009; Revised July 27, 2010; Published September 30, 2010; Online September 30, 2010

This paper introduces a new superquadric-based human body modeling technique. The model is used as part of an on-line path planning scheme. The path planning scheme utilizes a previously proposed danger evaluation metric in which danger is characterized based on human and nonhuman factors. A new factor that accounts for the human body orientation is introduced and used along with other factors for danger evaluation. A superquadric model of the human is used to determine the values of the factors used for danger evaluation including body orientation. The resulting danger value is then used to direct the search for an alternative robot path in a direction that minimizes the danger. The use of superquadric-based human model for danger evaluation and subsequently path planning provides an accurate and computationally efficient solution. At the same time, the resulting solution guarantees a safe and danger-free path, given the factors used to characterize the danger. The approach exhibits adequate speed of decision making, rendering it potentially suitable for real-time applications involving human-robot interaction. The proposed method is evaluated using a CRS-F3 industrial manipulator through various case studies.

Copyright © 2010 by American Society of Mechanical Engineers
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Figure 1

Orientation effect on distance of the robot to (a) the front and (b) the side of the human (top view)

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Figure 2

Frame assignment to the human body

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Figure 3

Modeling of abdominal intersection: (a) thickness and width and (b) superquadric shape (solid line) versus a circle (dashed line)

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Figure 4

(a) Contours with equal pseudodistances to the human body and (b) the orientation factor (σ=π/6 and Cα=5)

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Figure 5

A path consisting of straight lines and a circular arc

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Figure 6

The effect of measuring human body orientation in confined spaces. Top view of the generated path for (a) case 1 (α=0 rad), (b) case 2 (α=π/4 rad), and (c) case 3 (α=π/2 rad).

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Figure 7

Joint angle trajectories of the robot for cases 1–3

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Figure 10

Case 7: avoiding two obstacles simultaneously: (a) the desired path and (b) the top view of the motion

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Figure 11

Case 8: using an CRS-F3 industrial manipulator: (a) start point, (b) retraction to the first via point, (c) moving around the human to the second via point, (d) elevating the third link to avoid the object, (e) moving over the object, and (f) reaching the goal point

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Figure 12

Case 8; on-line path around two obstacles: (a) top view and (b) 3D view of the motion

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Figure 8

Cases 4 and 5: the resulting path (a) around and (b) over the human head based on the permissible danger levels

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Figure 9

Case 6: comparing the effect of the orientation factor: (a) fα=1 and (b) fα variables



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