IEEE Robotics & Automation Magazine - March 2023 - 76

p =+1 ip()
a
Xt
MB ut() () ().
t
Here
M = > +=>
Mm
+
aa
Mm H, DM
where () (()()) constitutes the
p tM MX tM Xt
=- D a
a
-1 po
+
2
uncertain environments of the RRDS, which differs based on
the rehabilitee. M is the mass of the RRDS, and m is the rehabilitee's
mass.
ESTIMATION OF HUMAN-ROBOT
UNCERTAIN ENVIRONMENTS
The SCN method was used to build a network identification
system model of human-robot uncertain environments,
and the motion trajectory and velocity were used as
the network inputs. The human-robot uncertainty environments
were obtained by the continuous and random
configuration of the hidden layer node. The workflow is
summarized as follows:
■ The motion trajectory and velocity () [( ), ()]
xt Xt Xt T
o
=
of
the RRDS are used as the network input layer of the SCN,
which is connected to the hidden layer through the weight
~ and threshold b, and the output (( ))Gx t of the hidden
layer is obtained using the Gaussian function. Here
[, ,, ], [, ,, ], (( )) [(
xt bg xt bQQ
~~ ff 11
T
== ~=
()
12
~~
Q bb bb Gx tg
T
T
++~
1), ..., (())].
12
Q
■ The SCN hidden layer is connected to the output layer
through the weight ,bt
and the network output
system uncertain environment is
bbT [, ,, ].Q12 fbb=tt tt
fp p=QQ
()
--t
tt
pQ
()t
t
pbT
=
t ()Q tG(( )),xt
t
■ According to the human-robot uncertain environment
error

IEEE Robotics & Automation Magazine - March 2023

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IEEE Robotics & Automation Magazine - March 2023 - Cover1
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