Fengtao Lin
email: menggu_lin@163.com

The Design and Simulation of Electro-Hydraulic Velocity Control System

Keywords: Electro-hydraulic servo system, Matlab, Simulation 1

In this paper, the principle of electro-hydraulic proportional control system are introduced, electro-hydraulic velocity control system are designed and can realize volevity control with high accuracy. In the system, relative amplitude abundant degree and phasic abundant degree and corresponding frequency of passing of Body system is easily obtained under different open ring gain of K, thus it is simple and accurate to choose reasonable parameters, and then can carry on smulation to system by Matlab/Simulink to examine the design results.

Introduction

Velocity control system [START_REF] Hongren | Hydraulic control system[END_REF]2]is widely used in practical projects need for velocity control, such as turrets, radar, turntable, etc; and the projects need for straight line motion velocity control, such as lifting platform, mail-sorting machine automatically conveyor, machine tool feeding device, etc. velocity control system with electro-hydraulic servo controller is a control circuit that output velocity variation feeds back to the input side via the sensor.

In electro-hydraulic velocity control system [START_REF] Eryilmaz | Unified Modeling and Analysis of a Proportional Valve[J][END_REF][START_REF] Liu | Research on the electrohydraulic variable valve actuation system based on a three-way proportional reducing Automovalve[END_REF] designing, the traditional approach is to identify the system composition and control mode based on the requirements, then to build the mathematical model and the system parameters, and adjust the open loop gain K of the system to ensure the system stability based on the bode diagram or nyquist diagram analysis of the open loop transfer function.

In this paper, open-loop transfer function of a system was described use matlab language, the amplitude margin, phase margin, and the corresponding crossover frequency of the relatively stable system can be calculated after evaluating the K value.

According to the critical condition of the system stability margin, the K value is adjusted and the new gain margin and phase margin were calculated repeatedly until at least one of the margins close to the critical condition steadily at the premise of all stability conditions are meet. and the parameters k value was decided. In this way, the open loop system amplitude and crossover frequency increased as much as possible, and also ensure the system stability. A rotating device velocity control system design of an equipment was presented as an example to illustrate the application of this method.

Methods and Applications

A device rotator system parameters are defined as follows [START_REF] Guan | Electro hydraulic Control Technique[END_REF]: Load rotational inertia , and performance index requirements are defined as follows: tracking precision is ±1 r /min, completing the tracking task accurately within 0.15 s.

J = 0.

Working principle of the contronl system

As the control power is smaller, so valve-controlled electro-hydraulic system [START_REF] Chunxing | Electro-Hydraulic Servo Control System[END_REF] is dominated directly by the servo valve. The working principle is shown by Fig. 1.

m θ & + - i u e u I L Q f u m θ & × Fig.1

. Diagram of system working principle

Where, i u is velocity contronl singal; e u is deviations;

I is input current; L Q is servo valve flow; ' m θ is output velocity; f u is feedback.

Motor discharge

In this paper, maximum load value is two-thirds of supply oil pressure value and is found to be: 2 2 8 10 5.3MPa 3 3

L P P = = × × = (1)
motor discharge is found to be:

Servo valve specifications determination

The servo valve flow is found to be:

θ & f u m θ & × + - 2 2 2 1 V V V V K s s ξ ω ω + + a K S 2 2 1 2 1 m V h h D s s ξ ω ω + + T K Fig. 2. Control system diagram 1
) the transfer function of electro-hydraulic servo valve the servo valve gain is defined as follows :

3 2

1.05 10 3.5 10 0.03

V V V Q K I - - × = = = × 3 1 m /s A - ⋅ (2)
Dynamic parameters of servo valve are decided in accordance with sample values, and natural frequency V ω is 340 rad / s, damping ratio V ξ is 0.70, so the transfer function expression can be prescripted as follows:

2 2 2 3.5 10 2 0.7 1 340 340

L Q s I s - × = × + + (3)
2)The transfer function of hydraulic motor By calculation, the total volume of motor oil cavity and the volume between servo valve to the motor is

Integral amplifier gain determination

Transfer function of open loop system is defined as follows: Wcg is the crossover frequency of the corresponding phase; m p is phase margin, Wcp is the crossover frequency of the corresponding amplitude.

Ka W S s s s s s - × × × × × =    × × + + + +       (7)
For the control engineering practice, stability margin must be ensured, so the parameters of the system are prescribed as follows:

m G > 6dB, that is: m G > 2; m p ≥ 30 ,
The system is single input-output system, the program designed as follows: The results are shown as follows:

Table 1.

Results of the program operation

In this paper, K =36.9 based on the analysis of table 1,and so there be:

W S s s s s s =     × × + + + +         (9)
2. [START_REF] Chunxing | Electro-Hydraulic Servo Control System[END_REF] The steady-state system error The open loop system is 1 type system because the introduction of an integral part. The error of system response to velocity instruction is zero, which can fully meet the tracking accuracy requirements of ± 1 r / min.

System simulation and results

System simulation diagram is shown by Fig. 3. and simulation results of system response to step signals is shown by Fig. 4. The simulation results show that the existing system is stable and non-overshoot, the increasing process was not monotonous, with a few small oscillations. the transition process within 0.11 s, and quickly reach convergence. so the system can complete the tracking task accuratly within 0.5s, the volecity control system design is meet the requirements very well.

Conclusion

1) In the velocity control system designing, relatively stable amplitude margin, phase margin, the crossover frequency of the corresponding phase and reasonable system parameters can be easy to calculated accurately based on the simulation of open loop system use matlab language,

2) simulation on the designed system using matlab/simulink can predict the results, verify correctness and provide a reference for designers. Availability of the simulation results depends on the correctness of the mathematical model, so rational model and parameters selection of the system are important.

  4 kg•m, rotational velocity range n =35 ~ 200 r/min, Working Pressure p =8MPa, Maximum load torque M =50N•m, static gain of velocity Sensor is 20V /1000 1 r min - ⋅

  cycloid hydraulic motor was selected, and the discharge m D

4 .

 4 valve can meet the parameters requirements, and it's rated no-load flows V The dynamic characteristic determination Control system diagram is shown as figure 2,where, a K is integral amplifier gain, V K is servo valve gain, V ξ is damping ratio of the servo vaulve, V ω is natural frequency of servo valva; m D is the hydraulic motor displacement, h ω is natural frequency of hydraulic motor, h ξ is the damping ratio of hydraulic motor.

  /rad transfer function of integral amplifier is defined as follows:

  Based on Bode diagram of the system, m G is the stable amplitude margin,

  sum = [K]; den1 = [1/340^2 1.4 /340 1 0 ] ; den2 = [0 1 /193^2 0.4 /193 1 ] ; den = conv(den1,den2); sys =tf(sum,den); Wcp =margin(sys)

Fig. 3 .Fig. 4 .

 34 Fig. 3. System simulation diagram

Acknowledgement. This work was sponsored by Supported by Foundation of Jiangxi Educational Committee(GJJ09210); Corresponding author: Fengtao Lin; Tel: 13970842969; E-mail: menggu_lin @163.com


Liyong Liu

, Qilong Pan

Daoliang Li
email: li_daoliang@yaohoo.com

P O Box

RESEARCH ON CALCULATION METHOD FOR AGRICULTURAL INFORMATIZATION CONTRIBUTION RATE

Keywords: agricultural informatization, contribution rate, index system, calculation

Informationization is the development trend around the world. In terms of agriculture, it is informationization that the Chinese government takes as a significant strategy in order to solve the 'agriculture, farmer and village' problem. Focusing on how to measure the contribution of agricultural informationization to economic growth, this paper explores several key issues in current literatures and summarizes the latest debates in respects of the concept of agricultural informationization, the evaluation method of agricultural informatization, and the calculation method of contribution rate of agricultural informationization to economic growth. This paper finally argues that further research is urgently needed for the contribution rate of agricultural informationization to economic growth due to the existing literature gap regarding the research scope, calculation method, informationization's impact on agriculture itself, and the practice.

INTRODUCTION

Agricultural informatization contribution rate refers to the proportion of algebraic summation in agricultural informatization contributed to in various production elements,or refers to the proportion of role played by agricultural informatization to the agricultural economic growth, and total agricultural output or total value of farm out-put are often used to state agricultural economy level. Agricultural informatization contribution rate will be an important comprehensive index that reflected agricultural informatization's function and role in agricultural production efficiency growth and agricultural economic development, and will also be an important index that reflected agricultural production mode and production level. Agricultural informatization contribution rate is still a new concept. Through consulting relevant literature in China and abroad, "informatization contribution rate ", Agricultural informatization contribution rate and their theoretical frontiers for calculation could be grasped well , and it is of great significance to understand scientifically agricultural informatization contribution rate and to further explore the calculation method which suits Chinese condition well.

There are several key problems needing to be solved when researching calculation method of agricultural informationization contribution rate. The first one is the definition of the concept and category of informatization and agricultural informatization. The second is measurement method of informatization and agricultural informatization level. The third one is measurement methods of the contribution rate of informatization to economic growth. The last one is the application of all measurement methods in agricultural informatization contribution rate. There has been much research on the aspects mentioned above, which provides study foundation for further work. So this paper mainly focuses on the summary and analysis of relevant literature in China and abroad.

RESEARCH ABOUT THE CONCEPT AND CONNOTATION OF AGRICULTURAL INFORMATIZATION

For the concept of the agricultural informatization, there has not been made an authoritative explanation in theory. Chunjiang [START_REF] Zhao | Rural informationization technology[END_REF] pointed out that agricultural informatization is a process, which, in human agricultural production activities and social practice, promotes agricultural economy development and the rural social progress by way of high-tech such as communications technology and information technology to efficiently make use of information resources. Shihong [START_REF] Liu | Information technology in agriculture and rural informatization[END_REF] pointed out agricultural informatization is a rural and agricultural integrated system including agricultural resources and environment informatization, rural social and economic informatization, agricultural production informatization, agricultural science and technology informatization, rural education informatization and agricultural production material and production management informatization. Fangquan [START_REF] Mei | Agriculture and rural information service: the diversification, the socialization and networking[END_REF] thinked agricultural informatization is a generalized concept, which is the wide application of information technology and information management in rural areas and should be informatization of agricultural overall process, and at least six fields, those are the informatization of rural life and consumption, the informationization of agricultural production management, the informationization of rural science and technology, the informationization of rural operation and management, the informatization of rural market circulation, and the informatization of rural resources and environment, should be included. Based on former research and some relevant conclusion, Daoliang [START_REF] Li | China's rural informatization development report[END_REF] and his team, make agricultural informatization as following definition: Agricultual informationization refers to a degree and process which modern information technology can be applied in rural production and business operation, rural public service, government management and daily consumption and other aspects through enhancing rural information infrastructure construction, such as broadcast networks, telecommunication network and computer network, fully developing and utilizing of information resources, structuring information service system, promoting information communication and knowledge sharing.

3.RESEARCH ON AGRICULTURAL INFORMATIZATION LEVEL MEASUREMENT

It is very different about the period, ways, speed and types of agricultural informatization around the world. In developed countries, study on agricultural informatization level measurement earlier was proceeded very early and have formed several mature development systems, which includs evaluation system. In the middle of 1980s, UNESCO proposed to use information utilization potential index method, and have done some practical measurement research (BroklH,Menou M.J. ,1982). In 1982, America's B.K.Eers used three-factors multiple-parameter model to analyze 87 underdeveloped countries' correlation of information activities with the social and economic development (Eres B k. 1982). Vijay S and William R K(1994)started wiht obtaining the competitive advantage and proposed evaluation index system of the enterprise's informatization, which included seven factors, totally twenty-nine indices. Ravi(1999)et al. started with keeping the competitive position and proposed to use 15 2nd indices to subdivide 1st index (key competition point) and to evaluate the enterprise informatization.. In order to evaluate enterprise informatization from the angle realizing the strategic objectives, Nagalingam (1997) used multiple-target comprehensive evaluation method and divided every strategic objective into several operational sub-objectives, which formed evaluation index system to be used in expert system. Under the condition of keeping China national informatization index system and Beijing informatization statistic index system identical and according to information basic elements and principles to establish evaluation index system, Anxiang Lu

THE STUDY OF CALCULATION METHODS OF INFORMATIZATION CONTRIBUTION RATE TO ECONOMIC

GROWTH

The theory of informatization measurement was originally proposed by American economists Fritz Machlup in his American Knowledge Production and Distribution in 1962. This measureing method is very wide, all-embracing in range, involving in various fields of intellectual industry. On the basis of Machlup, M. Poratm in 1977 put forward a new method system which is operative. The theory thinks that the development of information economy mainly depends on the development of two great information departments. The first department is that directly produces information and knowledge and then processes it. The second department is that consume information, namely all the the governments consuming information service and non-information enterprise. M.Poratm thought that the second information department plays an important role in information economy. For information economic input-output analysis, M.Poratm put forward a set of theories and methods of compiling information input-output table according to general input-output data, and used US national statistic data to concretely measure the employment and GNP value of information economy in US, which firstly makes people have a clear understanding to America's economic structure and nature.

Japanese economists Komatsu Kiyoshi in 1965 put forward informatization index method. This informatization index model is composed of 4 second indices and 11 third indices, including information amount (indirectly to show information equipment level and development level of information services' industry), information equipment rate, communication body level (personnel structure and the third industry development level), information coefficient (consumer's input besides the basic living expenses) and so on. This method is simple and easy to operate and has been widely used in many countries including China.

Compared with the developed countries, it is very late in China to study informationization. In the middle of 1980s China began to research on information theory and informatization level measure theory and methods. In 1997 Informationization Work Leading Group of the State Council put forward the definition of national informatization firstly.

When measuring informatization level in China, combining with China's specific situation and fully absorbing foreign existing scientific evaluation methods, Chinese scholars put forward some Chinese characteristic calculation methods of information contribution rate to economic growth. Youping [START_REF] Zhu | Discussion of informatization influence on economic growth[END_REF]used C-D Function to carry out regression analysis with Chinese real GDP data from 1980 to 1992 and information, capital and labor elements. The results showed that the information elements' contribution is the highest to the national economic growth (coefficient is 0.841597), the following one is labor elements (coefficient is 0.697838), and the last is the capital (coefficient is 0.255566). Based on output-growth production function, Dongqiang Guo, Zhijiang Wang (2000) put forward a mathematic model, which can measure contribution rate of informatization input to enterprise output growth, and provide theory basis for the quantitative evaluation of enterprise informatization's construction. According to Cobb-Douglas production function, Hua Zhou (2009) constructed a production function model which based on the informatization input. He took 54 electrical manufacturing enterprises informationization data in Fujian province from 2004 to 2006 as sample, and applied panel data analysis method to measure the output contribution coefficient of informatization.

RESEARCH ON MEASURING METHOD OF AGRICULTURAL INFORMATIZATION CONTRIBUTION RATE

Although there is amount of research in the measurement of contribution rate of informatization to economic growth in China and abroad, which accumulated much theory and a number of methods, and provides important reference for further research, From literature retrieval there is no statement of Agricultural informatization contribution rate up to now and study on contribution of agricultural informatization to agricultural economic growth is also very little. Xinran Zhao (2006) did a preliminary discussion of agricultural informatization input and output by way of cobb-douglas production function method in her master thesis, And the evaluation index of contribution of information input to agricultural economic growth was calculated by using the result of regression analysis.

Whether for the establishment of agricultural informatization evaluation system, or for construction of C-D production function, the argumentation for variable selection is still insufficient, leading to the lack of scientificity in conclusion and the vagueness of the concept of agricultural informatization. In addition, there is no directly relevant literature about agricultural informatization contribution rate. It is obviously a new research field to study the calculation method of agricultural informatization contribution rate.

6.CONCLUSION

To sum up, agricultural informatization contribution rate, as a comprehensive index reflecting the function of agricultural informatization in agricultural production efficiency and agricultural economic growth,, is still a new concept in academia. There is few direct research literature, and the research on theory and method is very short. But there is amount of research focusing on the informatization and measurement of agricultural informatization level, contribution rate of informatization to economic growth, which provide great foundation and many references to further study in theories and methods. Nonetheless, in those studies, there are still some problems needing to be solved. It is mainly in the following respects.

(1) As for the definition and concept of informationization, many definitions are basically limited to country, region. There are almost no statements on agricultural informatization or rural informatization abroad and most research are about the application of information technology in agriculture. Agricultural and rural informationization is an unique vocabulary under existing situation in China. The research scope of agricultural informatization is broad with different versions. Therefore, the principal task of research on agricultural informatization contribution rate is to clear the concept, connotation and extension of agricultural informatization based on the theory and practice in China and abroad.

(2) Although in the world there are dozens of methods of the informatization level measurement and analysis, the more common methods are Porat's method and the social informatization index model suggested by Japanese scholar, and both of them have their own advantages and disadvantages. Porat's method is a macro measure way, fitting for a national and social informatization, but it is not fit for agricultural informatization level measuring, because in China the concept of agricultural information industry is not clear. Japanese informatization index model neglectes the function of knowledge production department and information production department, which are very crucial in Porat's method. Informatization index method uses arithmetic average, which covers up some substantive difference. With the development of the times, the indices have seriously outdated, being hard to reflect the development trend and the latest achievements in informatization. In future, the research on index selection of agricultural informatization level measurement must fully consider the modern information technology development situation, such as the agricultural information technology application and promotion, etc.

(3) In the impact of informatization on economic and social development, existing research mainly concentrated on the impact of informatization on national economy, the difference of informatization level and informatization contribution rate between different countries, enterprise informatization and its benefit, etc. The research of contribution of informatization on agricultural development is very pool. Especially there are few studies on contribution rate of different informatization indices to agricultural development, leading to the shortage of scientific guidance when evaluating the efficiency of agricultural informatization construction.

(4) in the aspects of agricultural informatization level measurement and informatization contribution rate, most studies didn't deeply analyze the relationship and reciprocal influence between the informationization level and the efficiency difference, and couldn't provide feasible suggestions for national strategy and policies or measures. When trying to measure the contribution rate of agricultural informatization, it should pay much attention to the practical operation of informatization construction in future research.

Table 1

 1 , Yunlong Zhao, Xiangyang Qin, Zhihong Ma (2006) et al. proposed six aspects, from information resources development, informatization talents, construction of information network, application of information technology, consumptive level of information, and development level of information industry, including 19 indices to evaluate of rural informatization (

Table 1

 1 Agricultural informatization level evaluation index system (Anxiang[START_REF] Lu | Research on rural informationization measuring index system[END_REF]

	No.	Index	Unit
	1	Average hours radio and television broadcast per day	Hours/day
	2	Internet users per ten thousands person	Families/ 10000 persons
	3	bandwidth possession Per capita	KB/ person
	4	quantity of university students per ten thousands person	Persons/ ten
			thousands person
	5	Computer ownership rate per 100 Family	Sets/100 Family
	6	Lines of main toll route per 100 persons for fixed telephones	Lines/100 Family
	7	quantity of mobile phones per hundred person	Sets/100 person
	8	Rate of cable TV to premises	%
	9	The village owning cable rate (rate of the optical fibre cable to village)	%
	10	Broadband households rate(rate of broadband to premises)	%
	11	Information index	%
	12	Quantity of computer per hundred students, including college, middle	Sets/100 person
		school student
	13	Proportion of enterprises using internet enterprises to total enterprises	%
	14	Cable's length per 100 square kilometers	Core kilometers
			/100km 2
	15	total capacity of network resource database	G
	16	E-commerce transaction rate	%
	17	Rate of Information industry added-value to GDP	%
	18	proportion of fixed investment in information industry to fixed
		investment in whole society

% 19

Proportion of the expenses for information industry research and development to the expenses for whole social research and development %

ACKNOWLEDGEMENTS

The authors thank Ministry of Agriculture of People's Republic of China for it's financial support.


Anastasia Bolotnikova

Kévin Chappellet

Antonio Paolillo

Adrien Escande

Gholamreza Anbarjafari

Adolfo Suarez-Roos

Patrice Rabaté

Abderrahmane Kheddar

A circuit-breaker use-case operated by a humanoid in aircraft manufacturing

Automation of large-scale aircraft manufacturing with wheeled or embedded platforms requires costly changes of the manufacturing process and the environment. Humanoid robots could address this issue. We present a use-case of HRP-4 humanoid operating circuit-breakers. We show the feasibility of using visual feedback and force control in an integrated and unified multi-contact and multimodal task space quadratic programming (QP) whole-body control framework to enable HRP-4 to perform the task. We discuss the experimental results and outline the limitations of the current platform design and control implementation.

I. INTRODUCTION

Humanoid robots (humanoids) are gaining more maturity in terms of hardware and embedded software. Each year we witness the improvement of an existing series and the revelation of new platforms. So far, humanoids' developments have been confined to research, and there is still much to do in several specific aspects, e.g. robust dynamic walking, multi-contact behaviors or those common to general robotics research. As humanoids are getting close to well fulfil their functionalities in terms of locomotion and manipulation it is time to anticipate what they could be used for.

The first revealed applications of humanoids are oriented toward entertainments, e.g. [START_REF] Nakaoka | Intuitive and flexible user interface for creating whole body motions of biped humanoid robots[END_REF], [START_REF] Nakaoka | Toward the use of humanoid robots as assemblies of content technologies -realization of a biped humanoid robot allowing content creators to produce various expressions[END_REF]. Some applications target domotic assistance for frail persons 1 , where a humanoid can offer assistance services [START_REF] Pandey | Romeo2 project: Humanoid robot assistant and companion for everyday life: I. situation assessment for social intelligence[END_REF]. Recently the DARPA robotic challenge 2 opened potential applications in rescue and disaster operations. Yet the contest brought into light the gap that remains to overcome in order to efficiently deploy such a technology outdoor and achieve complex tasks such as driving [START_REF] Paolillo | Autonomous car driving by a humanoid robot[END_REF] or ladder climbing [START_REF] Vaillant | Multi-contact vertical ladder climbing with an HRP-2 humanoid[END_REF]. During the two previous years, we focused our efforts on applications of humanoids in manufacturing. There has been clear expression of the requirements by Airbus Group Innovation (AGI) for having humanoids operate in aerospace large-scale manufacturing and assembly lines, see section II.

In the frame of two on-going projects with AGI, this paper discusses the integration of our planning and control software components and knowledge in a first use-case consisting in operating circuit-breakers (pulling or pushing switches laid out in a panel), section II. This operation is found in the 1-University of Tartu, Estonia 2-CNRS-UM LIRMM, Interactive Digital Humans, Montpellier, France 3-CNRS-AIST Joint Robotics Laboratory, UMI3218/RL, Tsukuba, Japan 4-Department of Electrical and Electronic Engineering, HKU, Turkey 5-Airbus Group Innovation Center, Suresnes, France 1 http://http://www.projetromeo.com/ 2 http://www.theroboticschallenge.org/ manufacturing process and at the ground-testing operations of both airplanes and helicopters. We focus on demonstrating the feasibility of our multi-contact planning and control tools [START_REF] Bouyarmane | Humanoid robot locomotion and manipulation step planning[END_REF][7] [START_REF] Vaillant | Multi-contact vertical ladder climbing with an HRP-2 humanoid[END_REF] in this use-case. Our original contribution stands as follows:

• adding two functionalities to our whole-body quadratic programming (QP) control framework: we provide a multi-modal integration of force and visual servoing tasks in the framework together with other tasks such as fixed contacts, reaching, center-of-mass positioning, etc. (section III); • we extend our multi-contact planning to consider creating closed-kinematic chains, when possible, to fulfil the requirement of operating push/pull button task so that the humanoid equilibrium and pulling forces can be increased (section IV); • we demonstrate the circuit breaker checking task with the HRP-4 humanoid and discuss performances and limitations of the current set-up to be improved in nextstage developments (section V). Because of its primacy, we highlight the ambition behind deploying manufacturing humanoids in airliner assembly lines.

II. HUMANOID TECHNOLOGY IN AIRCRAFT

MANUFACTURING

At the Airbus airliners assembly lines, most of the assembly or system installation operations are achieved manually, especially those that have to be performed inside the aircraft. Robotic solutions have not found their way into all areas of aeronautical assembly lines because of safety, accessibility, weight, and the complexity of the operations to be performed. AGI developed a first prototype of a collaborative robot. This cobot, mainly composed of an intrinsically safe robot arm (Kuka LWR) mounted on an omnidirectional wheeled platform, is capable of performing some dedicated tasks inside an aircraft fuselage while sharing its workspace with several human workers. It is able to move on relatively flat floors, and to avoid obstacles.

Yet, there are still many manufacturing zones that cannot be reached by a wheeled cobot, e.g. in the cargo areas, cockpit, aisles. This is precisely where legged robots may be able to provide a more complete manufacturing solution, see Fig. 1. Furthermore, a wheeled cobot is confined to a given floor because it is not capable of autonomously moving to another platform within the same aircraft. While the installation of elevators could be a solution, it is costly and cannot be deployed everywhere. On the other hand, a humanoid platform would be free of this constraint since it can use the stairs already in place for human workers [START_REF] Caron | Multi-contact walking pattern generation based on model preview control of 3D COM accelerations[END_REF].

If we want to increase the level of automation, in order to make the shop floor productive and keep manufacturing plants in developed countries, we have to devise robots capable of:

• working in such confined, cluttered, and rugged areas;

• performing varying operations with standard manual tools (like humans); • moving autonomously through the manufacturing environment designed for humans. The motivation behind using humanoid technology is not solely driven by a wish to increase the level of automation. In fact, we mainly aim at addressing human workers health and safety issues. The goal is to use humanoids to perform "nonadded value tasks": repetitive tasks where the experience and intelligence of the operator are not put to use and where boredom can lead to mistakes, tasks presenting health risks such as anti-corrosion painting (highly toxic) or cleaning (after use of solvents, metallic dirt after drilling...) that are usually performed in confined spaces.

If safety requirements are met, a humanoid could perform a number of operations, such as:

• Accurate assembly operations, e.g. riveting, drilling and screwing using manual or semi-automatic hand tools; • Cleaning and painting operations;

• System installation: electrical harness installation, connector plugging, etc. Humanoids could also be used to perform other nonadded value tasks such as conveying equipment or tools to highly qualified operators: hundreds of thousand parts and tools are transported and manipulated by operators for each aircraft. By unburdening highly qualified operators from such boring tasks, a robot (even a costly humanoid) is socially and economically viable.

It is important to highlight that the introduction of humanoids in aeronautic plants should be facilitated because the aeronautic shop floor is a very well mastered environment:

• 3D models of the aircraft and the shop floors exist, enabling model-based reference and localization of the robot, • the Airbus operators are trained: they follow strict rules and assembly sequences, which will simplify humanhumanoid interaction. This study covers a frequent use-case encountered in production. It aims at investigating the capability (and hence the feasibility) of a humanoid to check the correct behavior of the electrical systems of the plane or helicopter once it has been assembled. Circuit breakers are used on aircrafts in order to protect an electrical circuit from damage caused by current excess. Their state can also be switched manually in order to reset operation or to switch off a function. In particular, during ground testing, operators manipulate the circuit breakers panel in order to validate the behavior of the systems in a large number of configurations.

The technological bottleneck concerns (i) navigation that we are addressing in the frame of the COMANOID3 project [8] using multi-contact technology [START_REF] Bouyarmane | Humanoid robot locomotion and manipulation step planning[END_REF], [START_REF] Escande | Planning contact points for humanoid robots[END_REF], [START_REF] Vaillant | Multi-contact vertical ladder climbing with an HRP-2 humanoid[END_REF], [START_REF] Brossette | Multi-contact postures computation on manifolds[END_REF] that is yet to be demonstrated with our humanoid in a 1:1 scale airplane mock-up, and (ii) once near the circuit-breaker panel, achieve the functional verification tasks and eventually report any encountered problem. For this purpose, AGI has provided a mock-up that is described in section V.

III. MULTIMODAL TASK SPACE QP CONTROL

To realize our use-case, the humanoid has to walk to the panel and stop nearby in an appropriate configuration (section IV). Then it has to lean on the panel with the (left) gripper that does not operate the switches (the reason for that and the methodology are explained in section IV), before starting to move the pulling tool attached to the (right) gripper using visual servoing in force-guarded motion, clamp the switch in the appropriate position, pull it under guarded motion and finally release the tool and start again with another switch. All these tasks have to be achieved under constraints of equilibrium, state (joint position, velocity and acceleration) limits, torque limits, non-sliding contact forces, no auto-collision, keeping the tracked marker in the field-ofview (FoV) of the camera, etc.

Multi-objective, task-space control [START_REF] Samson | Robot control-the task function approach[END_REF] formulated as quadratic programming appeared recently as a golden standard for whole-body control of humanoids, see examples in [START_REF] Sentis | Compliant control of mult-icontact and center-of-mass behaviors in humanoid robots[END_REF] [START_REF] Vaillant | Multi-contact vertical ladder climbing with an HRP-2 humanoid[END_REF]. Tasks can be ordered in strict, weighted or a hybrid priority. In a weighted (soft) priority scheme, that we are using, the tasks to be achieved at best are weighted according to their priority and summed in the cost function part of the QP. Those objectives that need to be fulfilled strictly are in the constraint part of the QP. For example, creating a contact is split into (i) a reaching contact task and (ii) a contact task. Reaching the contact is a task that is put first in the cost function. As soon as the contact is established, this task is removed and shifted into a QP constraint to maintain the contact. Tasks inclusions and removals, and changes of priority is scheduled and managed by a finite state machine, see section V and [START_REF] Vaillant | Multi-contact vertical ladder climbing with an HRP-2 humanoid[END_REF].

[12][13][14][15][16][17][18]
To be self-contained, we recall here the main ingredients of the QP control framework, with the classical tasks and the newly integrated ones: visual servoing and force control.

Each task T is defined as an error in the sensory space that is a function of the QP decision variable (robot state accelerations, torques, or applied forces) to which is associated:(i) a Jacobian matrix J, (ii) a weight that defines the soft priority w, and (iii) gains (namely, a stiffness k).

The most usual tasks are position-based (error between any point p robot (q) of the robot, like an end-effector position, center of mass (CoM) position... and a desired one). For N p such tasks with error T p = p robotp target , and weights w p , we write the cost function

P = N p ∑ p=1 w p Tp + 2 k p Ṫp + k p T p (1)
with Tp = J p q + Jp q. Tasks in position with strict inclusions, equalities and inequalities are integrated in the constraints part after two derivations that result in a linear form in the decision variables; they are gathered into P c . N v visual servoing tasks are defined as residuals in the task function space T v = ss target , s being the visual features, and s target their desired value. The time derivative of the residual is related to the joint velocities through the Jacobian J v = L v J, L v being the interaction matrix (i.e. the visual features Jacobian) and J being that of the robot as in classical visual servoing formulation. Hence, Ṫv = L v J q and its derivative Tv = Lv J q + L v Jv q + L v J q that is integrated in the cost function with weight w v and gain k v as

V = N v ∑ v=1 w v Tv + 2 k v Ṫv + k v T v (2)
More details on this formulation can be found in [START_REF] Agravante | Visual servoing in an optimization framework for the whole-body control of humanoid robots[END_REF]. Here also, visual tasks with strict inclusion, equalities or inequalities are integrated in the constraints part as previously and gathered in V c . Force control at a given robot operational point is implemented as an interplay between two functions. First, the target force f target can be either user defined f d or the output f of the QP controller. Let N f , be the number of force control tasks. Since the force f is a QP decision variable, if f d is defined, the force task writes simply as T f = ff d . In this latter case Ṫ f = T f = 0 by definition; it is the "QP force task" in Fig. 2. We also define an admittance task exactly in a form of a position-type one (previously discussed), where the Ṫ f = ṗrobotṗtarget such that ṗtarget = K f ( f targetf sensor )| n . ptarget and p target are obtained by numerical derivation and integration respectively; K f is a gain and n is the surface normal; this is the "QP admittance task" in Fig. 2. Finally,

F = N f ∑ f =1 w f T f + 2 k f Ṫ f + k f T f (3)
It is understood that eq. ( 3) splits in two tasks (force and admittance in Fig. 2) when f d is specified, and it is only the admittance task, when f d is not given by the user. As for previous task-types, inclusions, inequalities and equalities can be defined as constraints gathered in F c . At each control time step t, the controller with the set of tasks previously defined is fed back with the current state of the robot (q, q) and the sensors parameters. It then solves for the decision variables: robot state acceleration q, the stacked vector of forces f , and the actuation torques τ through the following QP: min

( q, f ,τ) P + V + F (4)
subject to: P c , V c , F c , plus the common additional ones as follows:

M(q) q +C(q, q) + G(q) = Sτ + J T f , (5)
the dynamic equation linking all the decision variables, with S a selection matrix for the actuated joints in q, J is the force to torques mapping Jacobian. M, C and G are the classical Inertia matrix and the Coriolis and Gravitation vectors respectively. Pre-multiplying this equation by S T , we can express τ as a affine function of q and f and remove it from the variables. We also have the kinematic (fixed) contact tasks as previously exemplified. Once the contact is reached, it is shifted into the constraint part of the QP through this task:

J q + J q = 0 (6)
The torque limits task inherent from the actuators characteristics are expressed as:

-τ max ≤ τ ≤ τ max (7)
Then we have:

A f ≤ 0, (8)
for non-sliding contacts. This task keeps the forces f within their linearized friction cones represented by A, see [START_REF] Caron | Leveraging cone double description for multi-contact stability of humanoids with applications to statics and dynamics[END_REF].

Collision avoidance is also integrated in the QP as described in [START_REF] Vaillant | Multi-contact vertical ladder climbing with an HRP-2 humanoid[END_REF]:

ḋ + t d ≥ ξ d -d σ d i -d σ ( 9
)
where d is the distance between a pair of bodies computed using [START_REF] Escande | A strictly convex hull for computing proximity distances with continuous gradient[END_REF], d σ is the threshold distance, under which we consider that collision happens; d i is the influence distance to activate the damping; ξ is a damping coefficient and t is the control time-step.

As in [START_REF] Vaillant | Multi-contact vertical ladder climbing with an HRP-2 humanoid[END_REF], waypoints tasks are integrated as guide-paths to avoid local minima. They also resolve the contradiction between moving a body to a desired contact spot and at the same time avoiding collision between that body and the environment component on which the contact is defined. Note that our controller integrates in a single formulation multiple robots (i.e. any objects, including other robots, that can be represented as robotic structures even with passive joint), see [START_REF] Vaillant | Multi-character physical and behavioural interactions controller[END_REF] [START_REF] Bouyarmane | Multirobot and force task-space control with quadratic programming[END_REF].

IV. TASK-AWARE CONTACT PLANNING

What makes humanoids a plausible perspective for their deployment in aerospace -or other large-scale productsmanufacturing, is their ability to use multi-contact technology, which has been the focus of our research and development in the past years [START_REF] Escande | Planning contact points for humanoid robots[END_REF][6] [START_REF] Vaillant | Multi-contact vertical ladder climbing with an HRP-2 humanoid[END_REF], see also 4 . Indeed, humanoid locomotion in cluttered environment exploits possible sequence of contact creations and removals between any part of the robot and the environment to plan motions. Robotic inhand and in-body object manipulation also exploits contacts and their repositioning for assembly operations. In fact, legs can enhance manipulation capabilities and grippers can enhance the locomotion ones. The two problems interchange in sharing the same background: they are governed by nonsmooth dynamics (friction and impacts at contacts) under limiting constraints including stability. Therefore, we have considered them jointly [START_REF] Bouyarmane | Humanoid robot locomotion and manipulation step planning[END_REF].

In the context of humanoid manufacturing, multi-contact capabilities come with an extra bonus: a humanoid can plan a contact to make a closed kinematic-chains that allows it to better sustain its equilibrium when needed or to apply higher forces thanks to internal torques. Let us exemplify this bonus with our circuit breaker scenario. The humanoid stands near the panel, and then pulls each switch one after the other. To pull the switch a force of about 13N is needed. Since humanoids have a floating base, the pulling force needs to be balanced by other contact forces. In preliminary experiments (section V), when the tool abruptly released the button during pulling, discontinuity in the applied force caused the robot to oscillate what could lead to balance loss if the force needed is high. Moreover, when pulling the switch (or a drawer or a door) the upper body may tend to lie toward it due to ankle flexibility if there is no postural counterbalance task.

In this example, if the humanoid put the palm of its other hand on the panel, it creates additional close kinematic chains (in addition to the existing ones due to feet contacts), which results in the robot being able to apply higher forces on the switch, generated from internal forces. It also prevents the robot from tilting toward the panel during pulling, and increases the equilibrium area and robustness.

The generalization of this concept is an on-going work that constitutes a substantial contribution to the multi-contact planning field in its own. As this contact planning is related to the task to be performed, we named it task-aware contact 4 www.comanoid.eu planning. We have two main ingredients to achieve this goal in this purpose study:

1) our current planning [START_REF] Bouyarmane | Humanoid robot locomotion and manipulation step planning[END_REF] and control [START_REF] Vaillant | Multi-character physical and behavioural interactions controller[END_REF] considers all manipulated objects and the environment as "robots" that are represented as a kinematic trees; 2) we recently devised a posture generator (PG) software that can compute static postures under a set of constraints including prevision on the applied forces (with equalities, bounds, inequalities) [START_REF] Brossette | Multi-contact postures computation on manifolds[END_REF]. We integrate the creation of such a contact, that is forcetask driven (instead of the locomotion-driven) to the general multi-contact planning context. Indeed, to add a contact what needs to be provided to the PG is:

1) the force to be applied and its location on the humanoid robot (according to a frame attached to the robot's link that will apply that force) and also a frame where in the other robots (i.e. the environment, the object, another robot...) it operates; 2) all the remaining humanoid robot's links, that are not in contact, paired with all the surfaces, where an additional contact can be added with a resultant force, that is greater in intensity to the task one with the opposite direction. The first step is provided by the manufacturing planner or the user. The second step boils to what is usually used in our general purpose multi-contact planning [START_REF] Escande | Planning contact points for humanoid robots[END_REF] [START_REF] Bouyarmane | Humanoid robot locomotion and manipulation step planning[END_REF]. But considering all the contact (link, surfaces) possibilities is certainly not a viable approach, and reducing the combinatorial search space is crucial in this context.

For example, let R env be the fixed environment, R rob be our humanoid, and R pan the panel system represented by N b + 1 links, where N b is the number of switches. In this case N b is also the number of prismatic joints of the panel system because the switch sockets are linked rigidly to R pan which in turn is rigidly linked to R env . We invoke the PG with the following task constraints:

• contact R rob 's left foot with R env 's ground (that can be fixed or free), • contact R rob 's right foot with R env 's ground (that can be fixed or free), • contact R rob 's right hand tool frame with a given R pan 's switch frame with n t . f c t ≥ f task , where n t is the contact normal, f c t is a decision variable of the PG and f task is the given (pulling) force; • contact R rob 's right hand palm with the R pan 's board (floating) with n t . f c p + n p . f c t as a cost to minimize, n p is the panel normal and f c p the contact force on the panel. The Figs. 3 and4 illustrate the obtained results for the panel with different switch positions. Notice that for each switch the posture returned is slightly different, which is normal. The resulting forces are rendered in red arrow (that of the left hand is shifted on the board, as otherwise it is not visible). In practice, we generated one posture at the center position and checked that all buttons are reachable by fixing the feet and the hand on the panel. Another solution, more costly, is to run a robot-duplicates optimization as in [START_REF] Vaillant | Multi-contact vertical ladder climbing with an HRP-2 humanoid[END_REF]. We can let the positioning of the feet to the PG of fixed them (typically in cluttered spaces). It is easy to understand, that with this additional panel contact, a sudden release of the pulling force still keeps the humanoid well balanced.

V. EXPERIMENTS AND RESULTS

A. Experimental set-up

The humanoid used for the experiments is the HRP-4. Xtion PRO LIVE camera is mounted in the head of HRP-4. It is placed in front of the panel with the circuit breakers (provided by AGI). The initial position does not have to be precisely set as planned in section IV, as visual feedback allows to perform the task successfully regardless of the variability in the starting position. Figure 5 shows one example of a feasible initial placement.

Switches on the panel are given a label based on the position in the 3 × 4 grid, that is switch i j , where i and j indicates the row and the column respectively.

Three WhyCon [START_REF] Nitsche | WhyCon: an efficient, marker-based localization system[END_REF] markers are placed in the panel to form a pattern, which is not ambiguous in rotation (e.g. "L" shape). One marker is attached to the tool, such that it remains visible throughout the experiment. The pulling tool is attached to the right wrist of the robot. Example of tool and marker placement is shown in Fig. 6. The horizontal offsets from one of the markers on the panel to the switch 00 are measured and later used to compute relative pose of the switch that needs to be pulled in the camera frame. Distance from the tool tip to the tool marker center d tc is measured

B. Finite-state machine

The entire experiment is managed by a finite state machine (FSM) composed by a finite set of states and transitions (t i ) between them. In each state appropriate tasks are either added to or removed from the QP. Figure 7 illustrates the FSM implementation for the circuit-breaker experiment. In the remaining part of this subsection, states and transitions of implemented FSM are described in more detail.

Initial posture is a safety state: CoM and torso orientation tasks must converge, before t1 can be triggered and further tasks are then added to the QP. In hand to panel state, position task is added to move left hand (LH) to a predefined way-point. t2 is triggered after position task converges. When in left hand admittance, position task for LH is removed. New contact constraint is added to ensure that left palm and panel are in contact. Admittance task with desired target force for the contact is added. t3 is triggered after desired force is achieved. In default position state, position task is added to move the right hand (RH) to default position through two predefined way-points. t4 is triggered once both waypoints have been reached sequentially. Image based visual servoing (IBVS) task is added in initialize gaze state, to ensure that markers appear in the FoV. Once IBVS error converges, t5 is triggered. After entering default position end, position task for RH is removed. Default position of the right hand with respect to the panel is refined by adding position based visual servoing (PBVS) task. Once vision based position of the tool is less than 3mm away from the target value, t6 is triggered. In wait for command, robot is waiting for the command with switch label (i j). After command is received, t7 is triggered.

In reach switch i j , the target for PBVS task is redefined, so that the tip of the tool is positioned under switch i j with appropriate offsets. t8 is triggered once tool tip is at least 3mm away from desired position. In the beginning of touch panel with tool tip PBVS task is removed. New forceguarded position task is added to detect when tool tip is in contact with the panel. When in contact (i.e. target force is reached), t9 is triggered. Set point task with objective to move RH 5mm back is added in move tool tip back state. t10 is triggered once set point task error converges. In tool admittance, set point task is removed. New contact constraint and admittance task are added to bring tip of the tool in contact with switch i j . After admittance task converges, t11 is triggered. In pull switch i j , set point task is added to move RH diagonally 1cm up and 2.5cm back to avoid tip of the tool slipping off the switch. As a result of this motion switch i j is pulled. t12 is triggered once Euclidean distance from the target position is less than 8mm. Contact between tool tip and the switch i j is removed in remove tool from switch i j state. After tool is removed away from the switch, t13 is triggered and robot goes back to default position end state.

C. Experimental results

For the discussion of results, we indicate main phases of the experiment as follows: 1) LH position task added, 2) LH admittance task added, 3) RH position task added, 4) IBVS task added, 5) PBVS task added, 6) switch label is received, 7) pulling finished, going back to default position.

Figure 8 demonstrates changes in HRP-4 joint values. As can be seen, the joint value curves are smooth with no abrupt changes. Figures 9 and 10 illustrate evolution of task error values during the experiment. Description of the tasks with corresponding weight and stiffness values is presented in Table I. As can be seen from the plot, high weight CoM task error stays close to zero, while lower weight torso orientation task error varies. Figure 10 illustrates fast convergence of IBVS, PBVS and LH position tasks to zero. Figure 11 illustrates the x-component of the LH force sensor that is controlled to hold a contact on a panel with a given desired force, and RH force sensors (we plotted the norm of all force components for RH). After phase 2, LH admittance task with force target -15N is added and force value converges to this target. LH admittance task is kept in the QP until the end of the experiment, and the controller tries to satisfy the objective while other motions are being performed. Fig. 11: The LH is controlled in admittance after phase (2) to hold a contact of -15N with the panel all along the experiment. We plotted the norm of all forces for the RH as in each step different components are used (guarded motion with its specific, putting the tool in the switch, pulling the switch and releasing it... all with different values of the desired force). These phases are clearly identifiable from the norm.

D. Performance evaluation

Stiffness of the tasks can be increased to force faster convergence of the error. However, when using visual feedback, there is a limitation on task convergence speed, due to the low frame rate of the standard camera. Task stiffness values used in QP controller are presented in Table I. Final size of the WhyCon markers used in the experiment, is 2.4cm (diameter of the outer black circle). In order to mini-mize amount of potential error in marker position estimation, maximal camera resolution was used for frame acquisition (1280×1024 pixels). This allowed to have 2-3mm precision in marker localization. Calibrated camera was used to ensure low uncertainty in the camera intrinsic parameters.

E. Discussions and limitations

The experiments were successfully conducted several times in the laboratory over the course of two months without imposing any explicit constraints on the light conditions of the room (both natural and electric light were used at some point). The same controller, with some additional improvements in the implementation, was used to demonstrate this work at the first Digital Festival in Tahiti in March of 2017. It was exposed to a large audience public, and demonstration at least 6 times per day, during 2 and half days with only one failure due to a wrong operation by the user. This shows, that our experiment is highly reproducible.

We used visual markers to better test motion planing part of the controller, without depending too much in lightning conditions of the experimental setup. Several types of marker trackers have been tested for application in the experiment (e.g. ARToolKit [START_REF] Kato | Marker tracking and HMD calibration for a video-based augmented reality conferencing system[END_REF] and other markers of similar type). The WhyCon marker proved to be most suitable for the application, as no false positive detection was encountered during the experiment and the accuracy of marker position estimation was sufficiently high for the task to be performed successfully. For the continuation of this work, more sophisticated solution for the visual feedback would require removing the markers from experimental setup and using visual primitives (e.g. keypoints, edges) to estimate location of the tool and the switch grid on the panel.

When estimating the state of the environment (i.e. switch and tool position) with non-maker-based computer vision methods, the amount of noise would likely increase and the smoothness of position estimation would drop. It is therefore critical to investigate the robustness of the visual servoing control w.r.t. to the measurement noise Limitation of the speed of visual servoing task depends on the image processing operation as well as the frame rate of the camera. High values of task speed may results in convergence prior to new frame acquisition and processing. As a result, the motion of the robot would be somehow jerky.

In circuit-breaker experiment, HRP-4 right hand wrist goes very close to the joint limit value, so do other joints of the upper legs. Also high variability in initial position can cause robot to be incapable of reaching some or all of the switches on the panel. It is thus evident, that with the current platform, performing the task successfully even in the open space without clutter or obstacles, can be challenging. In aircraft manufacturing, cluttered and confined spaces are recurrent and we recommend humanoid's design with higher redundancy and also large joint ranges. The limitation to this currently is not mechanical, but has to do with the cabling.

In the current implementation of controller, the tasks gains and their weightings are set manually. Those values, however, are not necessarily optimal. It is crucial to automate these settings using learning techniques for instance.

VI. CONCLUSION

We showed that HRP-4, controlled by multi-contact and multi-objective QP framework, can successfully perform circuit-breaker operating task. The controller design and QP tasks, including multi-modal integration of position, force and visual servoing tasks, have been presented and discussed. We demonstrate the advantage of creating closed kinematic chains as part of the multi-contact planning to increase balance robustness and task force range.

The experiment revealed that the humanoid design must have more redundancy to perform similar manufacturing tasks with higher flexibility and in more challenging environment. For the continuation of this work, non-marker-based visual feedback methods can be implemented and tested for full-body motion control in QP framework and methods to increase the execution speed can be investigated.

Fig. 1 :

 1 Fig. 1: Example of shop floors and environments (from left to right, top to down): the cargo area, the cockpit, the upper-area in two different phases of the assembly/installation. Notice the postures of the workers. A humanoid is expected to have such accessibility capabilities.

Fig. 2 :

 2 Fig. 2: Implementation of the force regulation within the QP framework.

Fig. 3 :Fig. 4 :

 34 Fig. 3: Output of the PG for the pulling task of two different buttons with f task =15N and 45N force. The feet are set at a fixed static position w.r.t the panel. Notice the difference in posture when the pulling force is higher and the buttons are different.

Fig. 5 :

 5 Fig. 5: Example of initial position.

Fig. 6 :

 6 Fig. 6: Marker and tool placement.

Fig. 7 :

 7 Fig. 7: FSM for circuit-breaker checking experiment.

Fig. 8 :

 8 Fig. 8: All HRP-4 joint values during the experiment.

Fig. 9 :

 9 Fig.9: General QP tasks: CoM and torso orientation task errors.

Fig. 10 :

 10 Fig. 10: Experiment specific task errors (normalized).

TABLE I :

 I QP tasks with weight and stiffness values.

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ACKNOWLEDGEMENTS

This work is supported in part from Airbus Group Innovation Center grants, H2020 COMANOID EU project, the CNRS-AIST-Airbus Group joint research program, the bpifrance ROMEO 2 PSPC project, the JSPS Grant-in-Aid for Scientific Research (B) Number 16H02886 ("Cutting-Edge multi-contact behaviors), and the French government research program "Investissements d'avenir" through the Robotex Equipment of Excellence (ANR-10-EQPX-44) for the HRP-4 humanoid robot.