DYNAMIC-BASED SIMULATION FOR HUMANOID ROBOT

WALKING USING WALKING SUPPORT SYSTEM

Aiman Musa M. Omer, Yu Ogura, Hideki Kondo

Graduate School of Science and Engineering, Waseda University, Tokyo, Japan

Hun-ok Lim

Department of Mechanical Engineering, Kanagawa University, Yokohama, Japan

Atsuo Takanishi

Department of Mechanical Engineering/ Humanoid Robotics Institute, Waseda University, Tokyo, Japan

Keywords: Dynamic Simulation, Humanoid Robot, Biped robot, Walking Assist Machine.

Abstract: A new humanoid bipedal robot WABIAN-2R was developed to simulate human motion. WABAIN-2R is

able to perform similar human-like walking motion. Moreover, the robot is able to perform walking motions

with a passive walk-assist machine. However, walking with an active walk-assist machine is expected to be

unstable. Conducting this experiment is highly risky and costly. Therefore, we had developed a dynamic

simulator in order to test walking robot with walk-assist machine before conducting it in real simulation.

1 INTRODUCTION

With the rapid aging of society in recent times, the

number of people with limb disabilities is increasing.

According to the research by the Health, Labour and

Welfare Ministry, Japan, there are around 1,749,000

people with limb disabilities; this accounts for more

than half of the total number of disabled people

(3,245,000 handicapped people) (Health). The

majority of these people suffer from lower-limb

disabilities. Therefore, the demands for establishing

a human walking model that can be adapted to

clinical medical treatment are increasing. Moreover,

this model is required for facilitating the

development of rehabilitation and medical welfare

instruments such as walking machines for assistance

or training (Figure 1(a)). However, experiments that

are carried out to estimate the effectiveness of such

machines by the elderly or handicapped could result

in serious bodily injury.

Many research groups have been studying biped

humanoid robots in order to realize the robots that

can coexist with humans and perform a variety of

tasks. For examples, a research group of HONDA

has developed the humanoid robots—P2, P3, and

ASIMO (Sakagami et. al, 2002).

(a) by human (b) by robot

Figure 1: Walk-assist machine.

The Japanese National Institute of Advanced

Industrial Science and Technology (AIST) and

Kawada Industries, Inc. have developed HRP-2P.

The University of Tokyo developed H6 and H7, and

the Technical University of Munich developed

Johnnie. Waseda University developed the

Musa M. Omer A., Ogura Y., Kondo H., Lim H. and Takanishi A. (2008).

DYNAMIC-BASED SIMULATION FOR HUMANOID ROBOT WALKING USING WALKING SUPPORT SYSTEM.

In Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - RA, pages 23-28

DOI: 10.5220/0001482100230028

 SciTePress

WABIAN series that realized various walking

motions by using moment compensation. Korea

Advanced Institute of Science and Technology

(KAIST) also developed a 41-DOF humanoid

robot— KHR-2 (Omer et. al, 2005).

The above mentioned human-size biped robots

achieved dynamic walking. If these humanoid robots

can use rehabilitation or welfare instruments as

shown in Figure 1(b), they will be able to help in

testing such instruments quantitatively. The main

advantages of the human simulator can be

considered to be as follows: (1) The measurement of

the angle and the torque required at each joint can be

measured easily and quantitatively as compared to

the corresponding values in the case of a human

measurement. (2) Experiments using such robots can

help identify leg defects of a human from an

engineering point of view. (3) A robot can replace

humans as experimental subjects in various

dangerous situations: experiments involving the

possibility of falling, tests with incomplete prototype

instruments, simulations of paralytic walks with

temporarily locked joints.

Such experiments require a humanoid robot that

enables it to closely replicate a human. However,

humans have more redundant DOFs than

conventional biped humanoid robots; this feature

enables them to achieve various motions. Therefore,

a DOF configuration that is necessary to reproduce

such motions is one of the very important issues in

the development of a humanoid robot (Ogura et. al,

2006).

The Waseda Bipedal Humanoid Robot

WABIAN-2R has been developed to simulate

human motion. WABIAN-2R performed human-like

walking motions (Figure 2). Moreover, WABIAN-

2R achieved to perform walking motion using walk-

assist machine. However, the walk-assist machine

was freely rolling without activating its wheels

motors. In this case, the robot faced the minimum

resistance or disturbance case by the walk-assist

machine. On the other hand, activating the walk-

assist machine may create a large disturbance for

robot due to separate control for each of them.

Conducting this experiment may be highly risky.

As we develop humanoid robot to coexist in the

human environment, we need to conduct many

experiments such as robot walking on uneven

surface, climbing the stairs, and robot interact with

other machine and instruments. Doing any new type

of experiment using WABIAN-2 might be risky.

Figure 2: WABIAN-2R.

Therefore, we need find a safer method for initial

experimental testing. Using a dynamic simulation is

useful method due to some reasons such as: (1) It is

safer in terms of cost and risk. (2) It is easy to

monitor and view motion outputs. (3) It can show

the variation cased by any external disturbances. In

this paper, a dynamic simulator is described, which

is able to easily simulate any new type of walking.

Using the dynamic simulator, we can monitor the

motion performance and output all needed data that

is useful for further development. This paper is

aimed to simulate the walking motions of

WABIAN-2 using walk-assist machine.

2 DYNAMIC SIMULATION

Dynamic simulation could be used to simulate the

dynamic motion of a mechanical structured model. It

can analyze the effects of the surrounding

environment on the mechanisms and objects. In

robotics researches, simulation software are used for

robotic simulation. There are many software used

for robotics simulation in different applications.

Most of those software are for industrial robot

applications. However, there are some software used

for mobile robot simulation. For examples,

RoboWorks, SD/FAST, OpenHRP, and Yobotics are

used for mobile and legged robot simulation.

Webots is high and advanced simulation software

used in Robotics simulation. It is use for prototyping

ICINCO 2008 - International Conference on Informatics in Control, Automation and Robotics

and simulation of mobile robots. It has many

advanced functions and techniques. Webots is very

easy to use and implement. Therefore, we choose it

as simulation software (Webots).

2.1 Modeling

In order to develop a dynamic simulation, we need

to go through several steps. First is modeling where

we set up the simulation environment and initial

parameters. We set up a full structure of WABIAN-2,

based on the specifications (size, shape, mass

distribution, friction, .etc) of components of

WABIAN-2 (Figure 3).

Figure 3: Modeled WABIAN-2R in the simulation world.

2.2 Controlling

Second is controlling, which identifies simulation

objects and controls the simulation procedures. The

controller is some how similar to the WABIAN-2R

control. It gets the input data from the CSV pattern

file, and sets the position angle of each joint through

inverse kinematics techniques. Moreover, the

controller sets the simulate time step and the

measurement of data.

2.3 Running

Lastly is the running of the simulation and checking

the dynamic motion. We can view the simulation

from different view sides which gives us a clear idea

about the simulation performance. Moreover, most

of the needed data could be measured through

several functions.

3 WALKING WITH WALKING

ASSIST MACHINE

WABIAN-2 performed some walking experiments

using walking assist machine. The performance was

conducted by leaning its arms on the walking assist

machine holder. The walking assist machine moves

passively without generating its own motion. The

robot was able to walk and push the walking assist

machine forward. The experiments were conducted

with different walking styles and different heights of

arm rest.

The walking performance of WABIAN-2 using

an active walking assist machine, expected to be

unstable. The walk-assist machine has its own

control system, not connected to WABIAN-2 control

system. The walking assist machine moves with

constant velocity in a forward direction, while the

robot moves by setting its position. The robot arms

may displace from its position on the arm rest of the

machine which will case external forces on

WABIAN-2. In order to stabilize the walking, the

external force has to be minimized.

Figure 4: WABIAN-2 with Walking Assist Machine.

DYNAMIC-BASED SIMULATION FOR HUMANOID ROBOT WALKING USING WALKING SUPPORT SYSTEM

3.1 Force Sensor

The real walking assist machine is developed to

sense the force applied by the load on the arm rest.

A force sensor is attached on the top of the arm rest

consisting of four displacement sensors. The

displacement sensor is simply a spring mechanism.

It senses forward and vertical forces and turns toque

by determining relative displacements between the

upper frame and the lower one (Figure 5). We can

develop the system that can adjust the velocity of the

walking assist machine in order to minimize the

displacement.

Figure 5: Force Sensor.

3.2 Velocity Control

There were some developments made on the

walking assist machine control system to adjust its

speed according to the force applied on the arm rest

(Egawa et. al, 1999). The arm rest is designed to

measure the force and torques applied by the user of

the machine (Figure 6). The controller uses those

measure data as an input data to set the velocity of

each motor of the machine (Figure 7). The force f

and the turning moment m which applied by the arm

of the user is calculated in the sensor by the

following equations:

= m + s

(1)

Figure 6: Force and Moment Applied to Arm rest.

Figure 7: Block Diagram for Control System.

where m

is the moment measured by the sensor, s

the distance shifted from the arm position to the

sensor position. The values for m

and f

are the

input data for the controller that set the velocity of

each wheel motor (Egawa et. al, 1999).

In this study, we have introduced a new control

system model that controls the velocity of the

walking assist machine. The system adjusts the

velocity according to the force measured by the

force sensor. The new adjusted velocity is based on

current velocity and the displacement with

WABIAN-2.

Developing the equations of the modeled system, we

can have the following equation:

= ma (2)

where m is the total mass of the walking assist

machine, a is the acceleration, and F

is the force

measured by the spring. The force is the result of

displacement of the spring mechanism, which can be

expressed as

= Cx (3)

where C is the spring constant and x is the amount of

displacement. Substitute equation (3) in (2), we will

have

a = (C/m) x (4)

the acceleration is the derivative of velocity.

Approximately, it is equal to the difference in

velocity over step, which could be express as

a(t) = (v (t + ∆t) – v (t)) / ∆t (5)

since we are dealing with discrete time, we can

rearrange equation (5) to

a(k) = (v(k+1) – v(k)) / T (6)

where v(k) is the current velocity, v(k+1) is the next

velocity, and T is the step time. Substitute equation

(4) in (6), we will have

v (k+1) = (C T /m) x(k) + v(k) (7)

where x(k) refer to the displacement measured by

the spring of the sensor. This equation represents the

velocity control process in the system.

ICINCO 2008 - International Conference on Informatics in Control, Automation and Robotics

4 SIMULATION RESULT

We test several types of motions performed by

WABIAN-2. The simulator simulates the walking

performance of conventional walking and stretch

walking (Figure 8). Moreover, it simulates some

other motions as the input pattern. The dynamic

simulation has given us a simulation motion just like

the real simulation. We monitor the simulation from

different viewpoints. Moreover, we could measure

some output data.

Figure 8: Simulation of different type of walking.

We conducted some simulation experiments of

walking using the walking assist machine. The robot

is able to walk stably with a passive walking assist

machine just like the real experiment (Figure 9). But

it was not possible to achieve the same result when

we conducted the experiment using an active

walking assist. As expected, the robot was affected

by the external force produced by its contact with

the walking assist machine. The robot became

unstable during its walking, and in some

experiments it fell down (Figure 10).

Figure 9: Simulation of walking with walk-assist machine.

Figure 10: Simulation of walking with active walking

machine.

By adding the force sensor to the simulated

walking assist machine, we were able to measure the

amount of external force acting on the robot. Using

these measurements with the velocity control we had

developed, the robot could walk with the active

walking assist machine. The amount of holding

torque we set to the walking assist machine wheels

could increase from 0.5 N.m to 0.75 N.m by using

this new velocity control in the control system of the

dynamic simulator we had developed (Figure 11).

Figure 11: Simulation of walking with the walking

machine using velocity control.

5 CONCLUSIONS AND FUTURE

WORK

This paper describes the simulation of walking by

WABIAN-2R with the walking assist machine. The

dynamic simulation is very important to check the

motion of any new pattern generated. Using the

dynamic simulation we can see the effect of the

DYNAMIC-BASED SIMULATION FOR HUMANOID ROBOT WALKING USING WALKING SUPPORT SYSTEM

walking assist on WABIAN-2R. As expected, the

walking was unstable due to the effect of external

forces created from the arm rest. By using the

velocity control in the control system of the

simulation, the robot is able to walk stably with the

walking assist machine.

In the near future, it is important to develop

WABIAN-2R system to be stabilized during

walking. The stabilization control will be based on

Zero Moment Point. Moreover, it is necessary to

develop the robot to interact with other objects and

equipments. This will make the robot can interact

with its surrounding environment.

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