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Purpose
In the industry, can reduce manpower and
improve efficiency
 can contribute to the restoration of some
functions lost by handicapped people
 medical assistance
 Do not need any one to help in 24 hours

Motivation

The handicapped people doesn’t accept an
assistive arm onto the wheelchair , because they
feel like being assimilated to a robot.

Manus® arm
Handicapped people takes the control of the
mobile robot and move the platform wherever he
wants and can also use the manipulator.
GLOBAL DESCRIPTION

It is made of two parts :
○ 1. the wheelchair equipped with a standard PC
and an interface screen and a joystick for
control .
○ 2. the mobile robot
equipped with two
omnidirectional
vision sensors
and a Manus® arm.

This robotic assistance will be used in:
○ Automatic mode: track and follow a wheelchair
autonomously without holding up the wheelchair.
○ Remote mode: Standing
close to the wheelchair
in order to be
manually controlled.
(this mode the
arm can be used )
THE OMNIDIRECTIONAL VISION

What is omnidirectional vision ?
A : Use only one camera, with a rotation motion
, in order to sweep a large space.
Disadvantage : the camera’s movement takes
time.

extend two classes of omnidirectional vision
systems :
1. the systems made of a mirror and a camera
are called 『 catadioptric systems 』 .
2. a classical camera with a fish-eye lens ,
such mountings are called 『 dioptric
systems 』.
THE AUTOMATIC TRACKING

The main goal is to enable the mobile robot to
track a wheelchair with no mark-up and no
particular equipment onto the wheelchair.

The omnidirectional vision is used in two
different ways :
○ 1. The free space map
○ 2. The tracking
The free space map

the two omnidirectional sensors are used as
goniometric sensors and compute distances of
the different verticals parts called natural
landmarks
Correspondences between angles from the left sensor to the right
sensor for objects situated at different distances from the mobile robot.
The tracking

As the wheelchair is not equipped with any
particular mark-up, we have to track it as it is,
so we use the CAMShift algorithm which
perform a tracking by using an image of the
object to track.

What is CAMShift?
A: Continuously Adaptive Mean Shift
CAMShift

Architecture
○ CAMShift是Mean Shift的改良版
○ CAMShift會更新每次搜索的範圍,更適合在連續
的影像中作物件追蹤

Step
○ 轉換HSV色彩空間
○ Back Projection
○ Mean Shift
○ CAMShift
CAMShift ’s Step

轉換成HSV色彩空間
○ 取得色彩直方圖
CAMShift ’s Step

Back Projection
CAMShift ’s Step

Mean Shift
○ 計算中心點
○ 旋轉的角度
CAMShift ’s step

選擇要追蹤的
物體
CAMShift
○ 將新得到的搜尋視窗，當
作第三步驟的初始搜尋視
窗。如此重複的執行，就
可以達到連續追蹤物件的
效果。
建立物體的色彩
直方圖
計算得到整個場
景的反向投影圖
重新對場景搜尋
搜尋視窗對準物
件的中心
CAMShift ’s defect
 背景過度複雜或是
有類似顏色的時候
效果會降低。
 物體本身就很複雜，
導致辨識困難或誤
判。
The tracking _ Initialization of
the CAMShift

In order to init the CAMShift, we need images
of the wheelchair.
○ compute the subtraction between the background
and the current image.
RESULTS
 CAMShift
:
www.youtube.com/watch?v=6rcTz1Iu
PGw&feature=related
 Manus® arm :
www.youtube.com/watch?v=LBUyiaA
PCcY