Novel Door-opening Method for Six-legged Robots Based on Only Force Sensing
Novel Door-opening Method for Six-legged Robots Based on Only Force Sensing
Zhi-Jun Chen 0 1
Feng Gao 0 1
Yang Pan 0 1
0 Shanghai GQY Robot Limited Company , Shanghai 201206 , China
1 Supported by National Natural Science Foundation of China (Grant Nos. U1613208, 51335007), National Basic Research Program of China (973 Program , Grant No. 2013CB035501) , Science Fund for Creative Research Groups of the National Natural Science Foundation of China (Grant No. 51421092), and Science and Technology Commission of Shanghai-based ''Innovation Action Plan'' Project , Grant No. 16DZ1201001
Current door-opening methods are mainly developed on tracked, wheeled and biped robots by applying multi-DOF manipulators and vision systems. However, door-opening methods for six-legged robots are seldom studied, especially using 0-DOF tools to operate and only force sensing to detect. A novel door-opening method for six-legged robots is developed and implemented to the six-parallel-legged robot. The kinematic model of the six-parallel-legged robot is established and the model of measuring the positional relationship between the robot and the door is proposed. The measurement model is completely based on only force sensing. The realtime trajectory planning method and the control strategy are designed. The trajectory planning method allows the maximum angle between the sagittal axis of the robot body and the normal line of the door plane to be 458. A 0-DOF tool mounted to the robot body is applied to operate. By integrating with the body, the tool has 6 DOFs and enough workspace to operate. The loose grasp achieved by the tool helps release the inner force in the tool. Experiments are carried out to validate the method. The results show that
Door-opening; Six-legged robots; Force sensing; 0-DOF tool
State Key Laboratory of Mechanical System and Vibration,
Shanghai Jiao Tong University, Shanghai 200240, China Shanghai GQY Robot Limited Company, Shanghai 201206, China
the method is effective and robust in opening doors wider
than 1 m. This paper proposes a novel door-opening
method for six-legged robots, which notably uses a 0-DOF
tool and only force sensing to detect and open the door.
Legged robots are believed to have better mobility in rough
terrain than tracked and wheeled robots, because they can
use isolated footholds to optimize support and traction [
So in disasters, such as earthquakes, nuclear and toxic
explosions which are too dangerous for human, legged
robots are expected to take the place of human to perform
rescue tasks. In indoor rescue, door-opening is a
fundamental and essential task, which has already been studied
for more than two decades [
]. However, current researches
on door-opening mostly focus on tracked [
] robots. In the field of legged robots, few
examples of biped and quadruped robots can be found. An
early example is the HRP2  in 2009 which was allowed
to hit a door open with its whole body. In recent years,
under the influence of the Defense Advanced Research
Projects Agency(DARPA) Robotics Challenge, more
related examples of biped robots opening doors can be found,
such as the HUBO [
], the ATLAS [
] and the COMAN
]. In 2015, Gonza´lez-Fierro, et al. [
] proposed a
method for humanoid robots to learn from demonstrations
of human opening doors, and defined a multi-objective
reward function as a measurement of the goal optimality.
Boston Dynamics’ MINISPOT  and Ghost Robotics’ MINITAUR  can open doors, but there is no related
paper about the details, and no related research on
sixlegged robots can be found. On the other hand, six-legged
robots can also adapt to complicated scenarios well and are
more stable when walking and operating. Therefore, it is
essential and helpful to develop a new method for
sixlegged robots to realize the function of opening doors.
When opening doors, robots mainly encounter two
issues. The first one is how to recognize and locate the door
and the handle in real time precisely in unknown
environments. In order to recognize and locate the handle,
vision systems such as laser scanners, cameras and infrared
sensors are always used. A few related works realize the
recognition of various door handles of unknown
geometries. Moreno, et al. [
] investigated different handle types
and applied a morphological filter adapted to the
characteristic shape of different handles to realize the recognition.
Klingbeil, et al. [
] used a computer vision and supervised
learning to identify 3D key locations on any handle, thus
choosing a manipulation strategy. Ignakov, et al. [
extracted the 3D point cloud of any unknown handle by
using the optical flow calculated from images taken with a
single CCD camera. Most other methods assume the
geometry of the handle is already known and the vision
systems are just used to locate. Adiwahono, et al. [
a Microsoft Kinect sensor and a 2D laser scanner to
estimate the handle position, thus planning the trajectory to
open the door. Petrovskaya, et al. [
] presented a unified,
real-time algorithm that simultaneously modeled the
position of the robot within the environment, as well as the
door and the handle. Kobayashi, et al. [
] applied an IP
camera and IR distance sensors to calculate the position of
the handle, which could be cylindrical with its diameter
48 mm to 56 mm or lever type. However, vision systems
are frequently subject to calibration errors, occlusions and
sight ranges, making it inevitable for scholars to apply
force sensing to additionally double-confirm the contact
position with the handle [
]. In fact, it is completely
competent for robots to use only force sensing to detect the
positional relationship with the door and the handle by
touching at different positions and different directions, just
like humans acting in the darkness. To simplify the system
and supplement relevant study, it is essential to develop a
new door-opening method based on only force sensing. If
the robot is far away from the door in an undiscovered
room, vision systems [
], human-computer interaction or
some other methods may be applied to help the robot
distinguish the door from the wall and navigate the robot to
the door, but not involved in measuring the positional
The second issue is how to release the inner force in the manipulator that occurs during turning the handle and pushing the door because of the positional error and the imprecise modeling of the environment. The inner force
occurs because the motion of the manipulator cannot
follow the position of the handle exactly due to the positional
error. In order to meet the positional accuracy
requirements, the manipulator must have at least three DOFs
theoretically, and specific mechanisms or control strategies
need to be applied. Farelo, et al. [
] designed a 9-DOF
wheelchair mounted robotic arm system to open doors by
keeping the end-effector stationary while moving the base
through the door. Ahmad, et al. and Zhang, et al. developed
a compact wrist which could switch between active mode
and passive mode as task requirements differed [
applied the wrist to a modular re-configurable robot
mounted to both a tracked mobile platform [
] and a
wheeled one [
] to open doors. Winiarski, et al. [
applied a direct impedance controller and a local stiffness
controller to a 7-DOF manipulator to robustly open doors.
Karayiannidis, et al. [
] proposed a dynamic
force/velocity controller which adaptively estimated the door
hinge’s position in real time, thus properly regulating the
forces and velocities in radial and tangential directions
during opening doors. Guo, et al. [
] simulated a hybrid
position/force controller for a manipulator mounted to a
wheeled platform to open doors. The PR2 [
both push and pull room doors and cabinets open by
applying vision systems, tactile sensors and an impedance
controller. However, the positional error cannot be
eliminated completely. The inner force still always occurs, as
long as the manipulator is compelled to follow the handle
exactly by a firm grasp. Considering that the firm grasp is
not essential for all cases, this paper applies a 0-DOF tool
which can effectively release the inner force by providing a
loose grasp and allowing relative movement between the
handle and the tool. By integrating with the 6-DOF body of
the robot, the 0-DOF tool mounted to the body has enough
DOFs and workspace to operate.
In this paper, a novel method for six-legged robots to
open doors autonomously is proposed and implemented to
the six-parallel-legged robot [
]. The method makes
the following contributions:
It is a novel method developed for six-legged robots to open doors.
The robot autonomously identifies its positional relationship with the door and the handle in real time based on only force sensing.
The robot uses a 0-DOF tool to operate, making a good use of the robot’s DOFs and workspace. The loose grasp of the tool effectively releases the inner force.
Experiments are carried out to validate the accuracy and robust of the method in unknown environments.
The rest part of this paper is organized as follows: in
Section 2 we introduce the system of the six-parallel
legged robot; in Section 3 we define the coordinate systems
and build the kinematic model of the robot; in Section 4 we
present the approach of opening a door and introduce the
subtasks in detail; in Section 5 we provide the experiment
results and discuss about them; in Section 6 we conclude
2 System Overview
Parallel mechanisms have been researched intensively and
applied widely [
]. But for robots with parallel legs,
few related examples can be found [
]. The platform
we study on is a six-parallel-legged robot as shown in
Fig. 1. The robot is a 6-DOF mobile platform with six legs
arranged symmetrically along the sagittal plane of the
body. Each leg of the robot is a 3-DOF parallel mechanism
with three chains: one universal joint - prismatic joint (UP)
chain, and two universal joint - prismatic joint - spherical
joint (UPS) chains. The prismatic joint of each chain is the
active input joint driven by a servo motor. A resolver is
mounted to each motor to feedback the real position of the
motor. At the head of the robot body, a 0-DOF tool with a
6D force sensor is mounted. The tool is composed of a
horizontal rod and a vertical rod, which are parallel to the
sagittal and vertical axis of the robot body respectively.
The 6D force sensor is the ATI Mini58 IP68 F/T Sensor.
Upside the body, a cabinet contains components of the
onboard control system, including the battery, the onboard
computer and the drivers.
Users control the robot by sending commands via a
remote terminal unit, which communicates with the
onboard computer via Wi-Fi. The resolvers provide the real
positions of all motors, and the 6D force sensor feeds back
the contact forces with the environments. The onboard
computer analyzes the positions and the forces data, and
accordingly plans the trajectories of the body and the feet.
According to the planed trajectories, the computer calcu
lates the parameters of all motors at every millisecond by
running the real-time Linux OS. After the calculation, the
onboard computer sends the parameters to the drivers via
EtherCAT. Finally, each driver generates a current proportional to the received parameter and provides the current to drive the relevant motor.
3 Coordinate Systems and Kinematic Model
3.1 Coordinate Systems Definition
In order to well express the positional relationships among
the door, the robot and the ground, it is essential to
establish five coordinate systems (Figures 2 and 3). The
first one is the Robot Coordinate System(RCS), which
locates at the center of the body and is fixed to the body. YR
and ZR are parallel to the vertical and sagittal axis of the
body respectively. The second one is the Ground
Coordinate System(GCS), which superposes the RCS at anywhere
the user sets and is fixed to the ground. So the RCS moves
together with the body and the GCS keeps still to the
ground. Here the GCS is set to superpose the RCS as the
door-opening task starts. The third one is the Door
Coordinate System(DCS), which locates at the intersection of
the handle axis and the door plane. The DCS is fixed to the
door, with ZD normal to the door plane and YD parallel to
the door hinge. The fourth one is the Leg Coordinate
System(LCS), which locates at the Ui1 joint of the UP
chain and is fixed to the body. When Ui1 is at its initial
position where every prismatic joint of leg i shrinks to the
shortest, XiL is along the prismatic joint, YiL and ZiL are
along the first and second axis of Ui1 respectively. The LCS
has a fixed relationship with the RCS defined by the
geometry of the robot, which can be denoted by iRLTði ¼
1; 2; . . .; 6Þ: The fifth one is the Ankle Coordinate
System(ACS), which locates at each ankle with the same
orientation as the LGS when Ui1 is at its initial position.
The ACS is fixed to the foot and moves as the leg moves.
3.2 Kinematic Model
Based on these coordinate systems, the kinematic model of
the robot can be built in the GCS, which is indispensable
for controlling the robot. The inverse kinematic model is
essential for assigning the position value of each actuation
in real time to generate the planed trajectories of the body
and the feet, and the forward kinematic model is essential
for calculating the real-time position of the robot.
As shown in Figure 3, let si denote OiASi1, hi1 and hi2
denote the first and second angle of Ui1, 2dUi and 2dSi denote
the lengths of Ui2Ui3 and Si2Si3, hUi and hSi denote the
tances from OiL to Ui2Ui3 and OiA to Si2Si3. Let Li(li1, li2, li3)
denote the lengths of Ui1Si1, Ui2Si2 and Ui3Si3, which is the
input of leg i. Let Si1(xi, yi, zi)T denote the coordinates of foot
i, which is the output of leg i. The output of the body can be
denoted by the pose matrix of the RCS in the GCS:
3.2.1 Inverse Kinematic Model
When given the output of the coordinates of all six feet and
the pose matrix of the RCS, the input of all prismatic joints
can be calculated in real time by
lij ¼ iiLARiASij þ iLOiA
where i—Leg number, i ¼ 1; 2; . . .; 6; j—Chain number of
leg i, j = 1, 2, 3,
0 cos hi1 cos hi2
sin hi1 cos hi2
cos hi1 sin hi2
sin hi1 sin hi2
sin hi1 1
i2 þ iLyi2 þ iLzi2
The hi1 and hi2 here can be calculated from the output
RGT and GSi1(Gxi, Gyi, Gzi)T by
>>> hi1 ¼ arctan
When given the input of all prismatic joints, either the
output coordinates of all six feet or the pose matrix of the
RCS must be known so that the other one can be derived. If the pose matrix of the RCS is known, the output coordinates of all six feet can be expressed by
8 RSi1 ¼ iRLT iiLARiASi1 þ iLOiA ;
>><>> GSi1 0 GGSO1R1 2¼GOkRRS1i1Tk02; RS11 1 T
>>>> RGR ¼ @ GS31 GOR A @ RS31 A
: GS51 GOR RS51
where i—Leg number, i = 1, 3, 5.
Here in Eqs. (4) and (5), the iiLAR, iLSi1 and iLOiA are
defined the same as in Eq. (2), but the hi1 and hi2 here are
calculated from the input Li(li1, li2, li3)T by
hSi sin hi2Þ
>>< hi2 ¼ arcsinðxiÞ
>>: hi1 ¼ arcsin
siÞ cos hi2
8> xi4 þ aixi3 þ bixi2
>>>>>>>>>>>>>>>> baii ¼¼ hUuiqi2ffiðffilffiffiiffi1dffiffiU2ffiffiffiiffidffisffiS2ffiiffiiÞffiffi2ffiffiþffiffiffiffihffiffi2Sffiffiiffi ;
/i2dS2i þ ui2
aixi þ ci ¼ 0;
>>> ci ¼
>>>> ui ¼
>:>>>>> /i ¼ li22
h2Ui ðli1 siÞ2þh2Si
siÞ2þdUi þ dSi þ hUi þ hSi
2 2 2 2
li22 þ li23 ;
4 Door-opening Method
The approach of the door-opening method is shown in
Figure 4, which can also be applied to pull doors with some
revisions on the trajectory planning. The task can be
decomposed into five subtasks: locating the door, rotating
to align, locating the handle, opening the door and walking
through. Here we use Q to denote the end-effecter of the
tool, and Q is fixed to the tool. The positions of Q at
different transients along the trajectory are marked by other
letters, and these marks are fixed to the ground.
4.1 Locating the Door
The first subtask is locating the door (O ? A?B ? C), in
which the robot identifies the orientation matrix of the DCS
in the GCS(GDR) by touching three non-collinear points on
the door, as shown in Figure 5.
Three non-collinear points define a plane. According to this basic principle, the robot firstly moves its body forward
Locate the door
Rotate to align
If force exceeds
Locate the handle
Open the door
Walk into door range
(–ZR) until Q touches the first point A on the
door (O ? A). Then, the robot moves its body both
backward and leftward to a different point (A ? O’), and
forward again to touch the second point B(O’ ? B).
Finally, the robot moves its body both backward and
upward (B ? O’’), and forward again to touch the third
point C(O’’ ? C). By making the backward and leftward
distance during AO’ equal, the backward and upward
distance during BO’’ equal, the maximum angle between the
sagittal axis of the robot body and the normal line of the
door plane is allowed to be 45 .
4.1.1 Trajectory Generation
The 6D trajectory of the robot body is generated by a discrete force control model:
8< M_ S€k ¼ Fk CS_k 1;
Sk ¼ S_k 1 þ S€kDt;
: Sk ¼ Sk 1 þ S_kDt;
Sk ¼ ðxk; yk; zk; ak; bk; ckÞT;
Fk—6D force at time k,
where Sk—6D coordinates of the robot body at time k,
By applying Eq. (5), GOR at A, B, C can be derived and
denoted as GORA(xA, yA, zA)T, GORB(xB, yB, zB)T and
GORC(xC, yC, zC)T. Let n(xn, yn, zn)T denote the normal
vector of the door plane. Then n can be calculated by
xB 1T0 Gxn 1
Transferring the vector n from the GCS to the RCS, we
Then projecting n into the XRORZR plane, we can get
Rnp ¼ ð Rxn
Here the Tait-Bryan angle, which includes roll, pitch and yaw, is used to express the orientation of the DCS in the GCS. The yaw angle is
Ya ¼ h ¼ arctan
Taking into account that there may be stairs or slopes
along the direction of ZD in front of the door, making the
door plane not normal to the ground plane, the pitch angle
exists between n and np:
Pi ¼ a ¼
Considering there is nearly no doors with stairs or slopes
along the direction of XD, we can reasonably assume that
the roll angle Ro ¼ 0:
So, the orientation matrix can be calculated from the
Tait-Bryan angle by
8 GR ¼ RGRORDRYX10Z00 ;
>> RDRYX0Z00 ðYa; Pi; RoÞ ¼ @B
4.2 Rotating to Align
0 cos h sin h sin a sin h cos a 1
0 cos a sin a CA:
sin h cos h sin a cos h cos a
The second subtask is rotating around XR and YR to align
with the door plane (C ? D). As shown in Figure 6, the
robot moves its body, both transferring and rotating, from
C to D, and at the same time moves the feet to follow the
body (CL ? DL). The point OR at D superposes OR at O,
which determines the 6D trajectory as
After the alignment, the horizontal rod of the tool will always keep normal to the door plane when the body translates, which guarantees the tool not to collide with the door plane during the process of locating the handle.
4.3 Locating the Handle
The third subtask is locating the han
dle (D ? E?F ? G), in which the robot identifies
translational parameter GOD by three touches in three
In order to touch the handle, the robot has to decide the height and the moving direction of the tool first. A
Robot CS YR
Figure 5 Locating the door plane
statistical analysis [
] of the most frequent size of handles
shows that the height of the handle is in a range from
99 cm to 103 cm. Based on this acknowledgement, the
robot keeps the vertical rod of the tool in this range. Then
the robot chooses right as its target direction to touch the
handle. If the robot confirms that the handle is not in the
current direction, it changes its direction to left and
performs the process of locating the handle again. Here we
present the process of the localization and confirmation of
the handle in the direction of right, and it is similar for left.
As shown in Figure 6, in case that the robot is far from the
handle, the robot needs to move rightward cyclically. In
every cycle except the final one, the robot successively
moves the body forward (–ZR) until touching the door plane,
backward for a short constant distance to avoid rubbing with
the door plane, rightward for a constant distance decided by
the workspace of the tool, and moves the legs to follow the
body, thus finishing the process of D ? E. The purpose of
moving forward to touch and backward for a constant
distance at the beginning of every cycle is to initialize the
Axis of the handle
distance of the current cycle and eliminate the error
accumulated in last one. When the robot starts too far from the
handle, a very little angular error will cause a large
translational error along ZD, even though the robot has already
rotated to align. The large error makes it highly possible for
the tool to fail to enter the space between the door and the
handle considering its narrowness, thus failing to open the
door. Because the distance of every rightward cycle is
limited to an acceptable constant value which will never be too
far, the translational error along ZD can be limited well.
Furthermore, by applying multiple three-points contacts of
locating the door and reducing the distance of every
rightward cycle, the detection accuracy can be guaranteed even if
there are embossments or grooves on the door.
In the final cycle (E ? F?G in Figure 7), after touching
something at F, the robot moves its body leftward for a
constant distance shorter than the handle, and downward to
touch the handle. If the tool touches nothing until it gets
lower than the minimum height, the robot treats it as a
confirmation that the handle is not in this direction. If the tool
touches something, the robot treats it as a signal of
successfully locating the handle and goes on to next subtask.
The trajectory is generated by Eq. (7) in every cycle.
The Fk of every cycle during D ? E is similar to the Fk of
E ? F in the final cycle, and in the final cycle the Fk is
>>>>8> 01ÞÞTT ; if Q 2 EE0;
>>>>>>> 10 ÞÞTT ; if Q 2 E0F0;
; if Q 2 FG0;
; if Q 2 FG0:
The location of OD on the handle can be expressed by
4.4 Opening the Door
The fourth subtask is opening the door (G ? H?I), in
which the robot firstly moves along a circular line in the door
plane to turn the handle until it reaches the end (G ? H in
Figure 8), and then moves forward to try to push the door
open (H ? I in Figure 8). When moving forward, the robot
keeps detecting the contact force. If it exceeds the maximum
force the robot can apply, the robot treats it as a signal of door
blocked and stops the task. The trajectories of turning and
pushing are both generated by Eq. (7), and the Fk is
>>>><> B@ RGRG sin 2vk
where v—Average linear speed planed along the arc, r—
Radius of the arc, Q 2 G_H—Q is on the arc _.
The simpler mechanism of the 0-DOF tool plays a
significant role here, in releasing the inner force in the tool when
turning the handle. The open-loop structure of the
end-effecter cannot achieve a firm grasp of the handle like widely
used closed-loop multi-DOF grippers, which takes a notably
positive effect on the subtask but not negative, because the
inner force is effectively released. The inner force occurs
because the motion of the manipulator cannot follow the
position of the handle exactly due to the positional error and
the imprecise modeling of the door, while a firm grasp
compels the manipulator to follow. And it is nearly
impossible to completely solve this confliction only if a firm grasp
is applied. However, the firm grasp is not essential for all
cases. When applying the loose grasp, the contact point of the
tool and the handle can slide along themselves, so that the
tool does not have to follow the handle exactly, thus releasing
the inner force. And because of the large areas the tool can
move in (red areas in Figure 8), it will not be a trouble for the
tool to keep contacting with the handle when moving.
4.5 Walking Through
The fifth subtask is walking through(I ? J?K ? L), in
which the robot adjusts its body back to the sagittal plane,
walks leftward into the door range, and then walks forward
to get through the door (Figure 9). The robot keeps
detecting the contact force during the whole process. If the
contact force exceeds the maximum force the robot can
apply, the robot treats it as a signal of door blocked and
stops the task.
When adjusting, the tool translates parallel to the wall
plane (I ? J) to release the handle and prepare for the left
walking. The point J is in the sagittal plane like the point E,
but higher than E for h to avoid colliding with the handle,
so the adjustment trajectory is
IJ ¼ BBB RGRI B@ RGRI RYR TðGE
RGRI ð 0
RGRI RXR TðGE
RGRJ ð 0
wR 1 1
2 CA CC;
where wR—Width of the robot.
During the process of walking forward, the robot uses its
body to push the door open, making a good use of the high
load capacity. The forward trajectory is
0 0 1 1
RGRK RZR TðGOD
RGRK ð 0
lR A ACC;
where RZR—Basis vector of Z-axis of the RCS,
RZR ¼ ð0; 0; 1ÞT;
GS41—Derived by Eq. (3), lR —Length of the robot.
In order to verify the proposed method, experiments were
carried out on the robot. The robot did not know the detailed
parameters of the environment and autonomously planed its
motion to open the door completely based on only the force
feedbacks in real time. The unknown environment here
means that the size of the door, the position of the handle, the
required force et al. are all unknown. The door is 2025 mm
high and 1130 mm wide, with a door closer to provide
rebound tendency, as shown in Figure 10. Figure 11 shows
the process of opening the door in the experiment.
During locating the door, the robot adjusted its position to
prepare for next touch every time when the force sensor
detected a force pulse along ZR which indicated the robot had
already touched the door. The robot only moved its body to
touch and kept its feet still on the ground. After detecting the
third touch, the robot calculated the positional relationship
with the door and rotated to keep the tool normal to the door
plane. During the alignment, the robot moved both its body
and feet. Figure 12 shows the positions of the feet and the
tool, and Figure 13 shows the force detected. Here we can
use the motions of feet 2 and 5 to show the motions of all feet,
because feet 2 and 5 move alternately in 3-3 gait.
Then, the robot moved rightward to touch the handle
and made different decisions based on different force
feedbacks. If no force pulse fed back, the robot moved its
legs to follow the body. If the force pulse along XR was
detected, the robot knew it had touched the handle, and
started to adjust its position to detect the handle along YR.
During this process, the robot moved its body and feet
separately. Figure 14 shows the positions of the feet and
the tool, and Figure 15 shows the force detected.
After detecting the force pulse along YR indicating that
the robot had touched the handle, the robot started to turn
the handle. Once the force feedback from the handle
exceeded the threshold indicating that the handle had
reached the end, the robot moved forward to push the door
open. Finally, the robot walked leftward into the door range
according to the calculated position of the handle and then
walked through. Figure 16 shows the positions of the feet
and the tool, and Figure 17 shows the force detected.
The method of measuring the positional relationship between the robot and the door is developed, which uses only the force sensing and the 0-DOF tool to detect and open the door.
The real-time trajectory planning method for the robot to open the door is proposed, which is completely based on the real-time measuring of the force sensing.
The proposed door-opening method is implemented
to the six-parallel-legged robot. Experiments are
carried out to validate the method and the results
show that the method is effective and robust in
opening doors wider than the robot (1 m) in
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Zhi-Jun Chen , born in 1991, is currently a PhD candidate at State Key Laboratory of Mechanical System and Vibration , Shanghai Jiao Tong University, Shanghai, China. He received his bachelor degree from Shanghai Jiao Tong University, China, in 2013 . His research interests include control and trajectory plan of legged robots . Tel: ? 86 - 15821788367 ; E-mail: Feng Gao, born in 1956, is currently a professor at State Key Laboratory of Mechanical System and Vibration , Shanghai Jiao Tong University, Shanghai, China. He received his PhD degree from Beihang University, China, in 1991 . His main research interests include parallel robots, design theory and its applications, large scale and heavy payload manipulator design, large scale press machine design and optimization, design and manufactory of nuclear power equipment, legged robots design and control. E-mail: Yang Pan, born in 1988, is currently working in Shanghai GQY Robot Limited Company, Shanghai, China. He received his PhD degree from Shanghai Jiao Tong University, China, in 2014 , and worked as a post-doctor at State Key Laboratory of Mechanical System and Vibration , Shanghai Jiao Tong University, China, until Jun. 2016 . His research interests include design and control of legged robots. E-mail: py0330@gmail .com