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Monday, October 8, 2012

WORLD ROBOTICS 2011 EXECUTIVE SUMMARY


World Robotics, 2011

Summary
                  The paper is the executive summary of World Robotics, showing the rend in the robotics market in the past years, with attention to the last one. In 2010 robot sales doubled compared to 2009 to 118,337 units, the main drivers of the strong recovery have been the electronics and automotive sector values for 2010 have got basically back to values pre-2009, which has been the worst year for robotics, the lowest from 1994.
If we go in details and check the areas where there has been a significative growth, then we will notice how Asia (including Australia and New Zeland) has faced a growth of 132% arriving to about 70,000 units/year.
The markets featuring the greatest dynamism, encountering a triple growth in the size of the market, have perhaps been China, Republic of Korea and in general the ASEAN countries.
In 2010 Japan, after leading for many years, for the first time fell down as the second largest robot market in the world, preceded by the Republic of Korea; China instead appears in forth position with its 15,000 units/year, thanks to an increase in capacities and in an increasing trend in towards automation.
In 2010 Italy, France, Spain, UK have all seen growth between 40% and 60%; these countries are particularly relevant since they are main countries for important automotive companies, a notable sector which faced a decreasing number of robot installation during the greatest economic downturns between 2006/07 and 2009.
The automotive industry has been the major market in the robot field, 70% of the robots in 2010 were demanded in this kind of application, it was followed by the electrical/electronic industry with a share of total supply of 26%. Surprisingly rubber and plastic industry, after years of increasing market share, has seen a reduction in its supplies.
Since the end of the 60s, when the first industrial robots were introduced, the cumulated sales of robots has been of 2,142,000 units up to the end of 2010. On the assumption that the service life of a robot is in average between 12 years (according to the World Robotics Executive Summary 2011) and 15 Years (according to a UNECE/IFR pilot study), we might say that at the end of year 2010 the world wide stock of operational robots was in the range of 1,035,000 and 1,300,000 units.
In 2010 sales recovered by 50% compared with 2009, it reached a value up to 5.7 billion $, still below 2008, one of the most successful years ever. In year 2010 the values of the market (without counting peripherals, such as $, software and system engineering) was estimated as 5.7 billion, the world wide market value for robot systems in 2010 is so estimated to be 17.5 billion $ if keeping into account peripherals.
The world’s robot density by the end of 2010 was about 50 industrial robots in operation per 10,000 employees in manufacturing industry, seeing stagnation in Japan (which still leads), an increasing growth in South Korean and Germany which are following up. 
The automotive industry has a much higher rate of automation, reason why for example in Japan the automotive industry has 1,436 industrial robots installed per 10,000 persons employed, while for the other industries the density goes down to 191. In the US in the automotive sector there are 1,112 industrial robot per 10,000 employees, but only 69 in the other sectors. China has seen an interested increase, between 2006 and 2010 the industrial robots density grew from 37 to 105 in the automotive sector, while other sectors passed from 30 to 86. For year 2011 a growth in robots installations is expected to be about 18% and Japan, thanks to new project, is expected to get back the leading position as robot maker.
China is expected to be one of the top robot makers by 2014. Service Robots are still on the way, there have been in 2009 a growth of 4% and the market is estimated to value 3,2 billion $. Applications of course still see a great participation of the defense sector, covering 45% of the market; medical robots follow with 14% and Logistics with 7%.
Key Concepts
Market

Human-robot cooperation control for installing heavy construction materials


Seung Yeol Lee, Kye Young Lee, Sang Heon Lee
Autonomous Robots, N0.22, 2007

Summary
                  Automation System and Robotic Construction is an issue which has came to discussion among researched due to the importance of safety, productivity, quality and work environment. The first robot applied in construction field was in 1983, followed by other examples of robots using pneumatic actuators and servo motors in hybrid solutions or in master-slave solutions. With the new trend of tall and dangerous buildings, advances in new material have be done, but still the process remains mainly assigned to manpower. An automation system (ASCI: Automation System for Curtain Wall Installation) has been developed for mechanized construction to enable simple and precise installations, specially in regard of safety improvement. Automation in construction faces some characteristics which make it much different from manufacturing, in fact rarely processes are highly repetitive, therefore the requirements for this system are: the robot must follow the operator in various works, a robot must share the work space with the operator, there must be coordination between the operator’s and the robot’s force and an intuitive operation method that reflect dexterity of an operator should be performed. Human robot cooperation has been an interest for many different fields of application, in the 60’s the department of defence enhanced the capability of carrying heavy material with “Suit of Armor” and similar ideas where carried later on.  The paper introduces a robot control method for the installation of heavy construction material in cooperation with a human operator, basically the system allows the operator to handle heavy material by exerting operational force with a certain power assist ratio. Target dynamics model the interactions among human, robot and environment, an impendance controller which considers each environment contacting is performed considering two cases: constrained and unconstrained, which differ in the presence or not of environment contact. In unconstrained condition the operator handle heavy materials on an obstacle free area, the force is measured by a force (torque) sensor, Fh(T) is the force generated by the interaction between the operator and a heavy material, Mpt(Mot) and Bpt(Bot) are respectively the n x n positive definite diagonal inertia and damping matrices. The desired dynamics, given input Ff,(Th) is obtained by impedance, by means of λp and λo, respectively the power assist ration of the position and orientation. The Stiffness Matrices is K is to not be considered having the property of a spring.  Constrained condition differed in the presence in the impedance of Fe(Te), the experimental force (torque) and in this case, if contact occurs the generalized active impedance is considered. High stability is achieved s through damping, where too much damping may decrease mobility of the system so Mpt(Mot) and Bpt(Bot) are adjusted according to the requirements of the operator and appropriate values are found through simulation. Motion control is made stiffness so as enhance disturbance disturbance rejection, so a reference frame and a desired frame are introduced in the previous models. Experiment have been carried on requiring the operator to perform a circle applying force on the robot’s gripper.
Key Concepts
Human Robot Interaction, Human Robot Cooperation, Impedance Control, Control Systems
Key Results
The results show that and increase in Mpt(Mot) stability decreases (although the with the increase of Mpt an object can move to a long-distance place with small operational force), while the opposite is for Bpt(Bot), making it necessary to make a trade-off.
Also it is shown that a robot operation without the inner motion control (which balances the system) shows inferior desired position following performance in an unconstrained condition.
The force required by an operator gets smaller with higher values of the power ratio, but this won’t cause hang in Fe (force that reflect in the contacting condition.

Human-Assisted Virtual Environment Modeling


J.G. Wang, Y.F. Li
Autonomous Robots, N0.6, 1999

Summary
                  The paper proposes a man-machine interaction based on stereo-vision system. where the operator’s knowledge about the system is used as a guidance for modelling a 3D environment.
Virtual Environment (VE) modelling appears to be a key point in many robotic systems, specially in regard of tele-robotics. There have been many researches on how to build VE starting from vision sensors while exploring unknown environments and semi-automatic modelling with minimum human interaction. A good example of integrated robotic manipulator system using virtual reality (Chen and Trivedi, 1993, Trivedi and Chen, 1993) visualization to create advanced, flexible and intelligent user interfaces. An interactive modelling system was proposed in order to model remote physical environments through two CCD cameras, where edge information is used for stereo-matching and triangulation to extract shape information, but the system was constrained by the only motion of the camera on the Z axis.
The proposed system is performing in order that the operator can minimize the cues about the features and information the manipulator or mobile robot may encounter. The procedure followed sees first a local model build from different view point and later these local models composing a global model for the environment, once the environment has been constructed virtually, then the operator can fully concentrate in tele-operation.
Considering the use of two cameras, left and right, then two transformation matrices can be obtained: [HR] and [HL] these can be used for calculating W, the corresponding known image coordinate feature points of the 3D coordinate feature points. So in the end, assuming the 3D vector in W as [V3D] and the correspondent 2D vector [V2D], then [H]= [V2D] [V3D]T[[V3D] [V3D]T]-1 , where H can be decomposed in left and right matrices. Further on, if we assume [HR] and [HL] available, [X]=[x,y,z] of a feature in W can be calculated with its corresponding image coordinates [xa ya], [xb yb], so that [X]=[[A]T[A]]-1[A]T[B], where [A] and [B] are image coordinates.
A major difficulty though in stereo vision is the correspondence problem between the feature points in two images, due to poor robustness. A human operator can therefore identify objects in most of the scenes, prompting the vision system to locate and detect some object attributes or special corresponding feature so that the image coordinates would be deducted and the 3D position in W calculated.
A binocular stereo vision, after been guided by an operator to find some correspondent prompted feature, can be used to construct the local models of objects directly. The system work in recognizing primitive solids, from which is later possible to computer composite models. The authors introduce the cuboid (for which four points are detected) and the sphere (for which determination in a 3D space is obtained through the knowledge of radius and center), which through geometrical calculations and transformations can be obtained. Vertexes of objects are found through the intersection of corresponding lines, for other more complicated objects operator’s guidance can be used. In general only one point of view cannot successfully represent a 3D object, more than one is required and therefore Multi-Viewpoint Modelling is used. Therefore from two positions (for instance A and B) a transformation M-1 takes place, determining M rotation and translation are solved separately. If C and C’ represent the coordinate relationships between view point A and B, then C’=M’C and W=M’W’; after some computation M=[R T], with R rotational component and T translational component.
Key Concepts
Machine vision, Human Robot Interaction
Key Results
Performance can be studied either with different between point and their image or with the different between measured and real size objects. The system also work with insertion tasks with an error of 0.6 mm, in case of the need of a more precise system, force sensing would then be needed. Operators can use this methodology for observing real environment from any view points on the virtual reality system.

Information Sharing via Projection Function for Coexistence of Robot and Human


Yujin Wakita, Shigeoki Hirai, Takashi Suehiro, Toshio Hori
Autonomous Robots, N0.10, 2001

Summary
                  The authors introduce the concept of safety based on intelligent augmentation of robotic systems. In previous studies the authors introduced the concept of tele-robotic systems (1992,1995,1996), where a robot is operated from another position with no physical contact and monitored through a television, and intelligent monitoring (1992), a system allowing conveyance of only required information through selection of data. The expansion of this last system has been the snapshot function (1995), where a laser pointer helps in teaching mode to estimate the deviation of the position, while the operator can move the robot, teaching the estimated relative deviation. A further implementation is the here proposed projection function (2001), where a robot and human jointly operate through a Digital Desk, a special environment provided with a projector perpendicular to the working table and a speaker. The aim of this research is to achieve intelligent augmentation in order to prevent and avoid undesirable contact, information sharing is a fundamental aspect in cooperative tasks between a person and a robot (Wakita, 1998). The experiment test a human and robot operating in mainly 5 states (initial, approach, grasp, release and final), the main issue is this kind of problem to be solves are: the person does not know the delivery coordinate, the person must keep holding the object until it is released, the person might be frightened by the robot movement.
The projection function consists of projecting on the table the simulated images of the moving robot, so that the human operator knows in real time the robots trajectory and understand the delivery trajectory. Force sensors in the robot’s fingers are used in order to allow the robot understand when the object has been grasped by the operator. A new teaching method also is introduced: the operator activated the teaching mode by touching the robot’s hand, then, instead of physically moving the manipulator, the projected image of the robot follows the operator’s hand to destination, the advantage is that only the model is required and no robot movement; the robot confirm through the speakers that the teaching trajectory has been saved.
The force sensors are an efficient communication method only during grasping, visual monitoring appears to be necessary for the entire delivery task.
It can be observed that humans in cooperation require visual feedback in order to understand that their motion and activity has been understood, each person expects to be observed during their action. So visual information appears to be extremely important by means of perception and it enhance safety in the system.
The digital desks comes to help once again in monitoring and indicating robots and humans in the system, in fact while operating a symbol (in the experiment it is a white rectangle) is projected on the hand of the operator when the robot has detected an action, in this way the human is aware that the robot knows about its presence.
In order to perform the experiment, a CCD camera was used for detection of human’s hand and robot position, and a video projector (SANYO LP-SG60) mounted on the ceiling in parallel with the camera.
The system as programmed, projects a white rectangle on the human’s hand when the CCD and the computer had performed the detection, while stationary hand is recognized a the delivery position.
Key Concepts
Human-Robot Interaction, Human-Robot Cooperation, Team Working
Key Results
The experiment appears to be useful prompting the importance of communication between robots and humans working together, a communication which need also visual feedback in order to ensure safety. A big part of communication is in fact performed not only by direct communication, but also by indirect feedback, showing that the message has been properly received. Future research may require adding information to the system.

Flexibility as processes mobility: The management of plant capabilities for quick response manufacturing


David M. Upton
Journal of Operations Management, No. 12, 1995

Summary
                  Improvement in flexibility is a key point of achieving achievements in competition in manufacturing, but at the same time the vagueness of the term determined at the same time its weakness. Flexibility can be distinguished among the internal capability of being flexible (capability) or the extern competitive need (mobility, Uton,1994). Another form of flexibility and be expressed by the ability of producing a wide range of products. Flexibility in academic is often relevant in the literature to four primary sources: economics, decision science, competitive strategy and manufacturing management. Different definitions have been taken, the author uses the following definition “flexibility as the ability to change with little penalty in time, effort, cost or time” and therefore he investigates the ability to change the product being manufactured, analysing in deep the context of mobility. The author visited 52 plants in North-America in the uncoated fine paper industry in 2 years, it’s an industry characterized by a growing need of flexible operations and often not able to achieve JIT, ending up with inventory and loosing money. The author interviews Vice-Presidents for Operations, COO, plant managers, paper machine superintendents and operators. The kind of industry is a typical low-cost product, where a plant has to hold a competitive price, the plants no able to remain competitive in cost have to be forced to stay busy since they have to balance pulp flow and continue to add value in the plant, so that flexibility appears to be an extreme point for a small and middle companies to survive. Changeover in this kind of production is also not easy to do complexity in operation, so that the goal is to perform change as swiftly as possible, a different degree of automation can be observed among companies and even operator may view it as a slowing and inflexible factor. Time to change grade on a machine appear then affected by: Plant Operations policies, Plant structure, Plant infrastructure and Managerial Emphasis. Plant operations policy is characterized by dimension of change (in colour, furnish, basis weight and calibre), magnitude (the time to effect change increases with the magnitude of the change, this is why often in the market production cycles are running on a two-week basis) and change frequency (plants which make frequent changes might be expected to make faster grade changes). The Plant structure is characterize on scale (increasing scale results in greater mechanical inertia of the components, and pressure that operator may impose themselves to change quickly may increase the cost of losing production on a big plant) and technology vintage (older low level technology may inhibit the ability of the plants operator to change). The plant infrastructure is characterized by computer integration (this may provide greater integration)and workforce experience (low levels increase time to change). Under the managerial point of view, flexibility appears to be a cultural background of the company and managerial approach.
Key Concepts
Flexibility
Key Results
It is clear that, in case of non-fully-automated processes, it is not possible to engineer a flexible approach, but relations between factors can be cleared and levels can be defined according on the market situation. The author, carrying different measurements to verify the factory describes above has shown different aspects for faster and older machines result in faster basis weight changes, while automation carried on general and repetitive task does not push the system to changes. Interesting is that each extra year of crew service is associated with four extra minutes taken to change grade, the crew experience causes inflexibility, but it is not related with any physical impediment due to age. Also interesting is that quick change overs are characterized with smaller change times. In the end it appears that a clear understanding of capability of flexibility is needed to fully access the tools of flexibility