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Concept for Human Robot Co-operation Integrating Arificial Haptic Perception

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Concept for Human Robot Co-operationIntegrating Artificial Haptic PerceptionCatherina Burghart, Sadi Yigit, Oliver Kerpa, Dirk Osswald, and Heinz WoernInstitute of Process Control & Robotics,University of Karlsruhe,D-76128 Karlsruhe, Germany.{burghart, yigit, kerpa, osswald, woern}@a.deAbstract. Human robot co-operation becomes more and more important when usingrobots in daily life and is a key note in the design of humanoid robots. The authorsare members of the newly founded centre of excellence “Humanoid robots – co-operating and learning systems” at the University of Karlsruhe. Our group ofresearchers is responsible for the human robot co-operation, a haptic sensor systemand the control of a robot hand. All three topics closely co-operate as the humanrobot co-operation (using a robot arm and a robot hand attached to it) is mainlybased on the haptic sensor system within the first phase of the project. In this paperwe present our first classifications for human robot co-operation and contactsbetween a robot and a human or an object, which both form the basis for ourpractical work. The control concept of our robotic system is depicted as well.1. IntroductionAt the University of Karlsruhe a new centre of excellence titled “Humanoid robots – co-operating and learning systems” has been founded which focuses on the perception and the modelling of the environment of a humanoid robot (including humans) and the co-operation between human and robot. Within this scope the authors of this paper are responsible for the design and transposition of the human robot co-operation, for the design and integration of haptic sensibility and the control of a five fingered robot hand. For this purpose we use a robot arm with seven degrees of freedom and a five fingered hand attached to it as first test bed. Later, results will be transposed to a humanoid robot designed by other groups within the centre of excellence.Haptic sensors form the basis of the human robot co-operation within the first phase of the project. They are used as a means of a human user to directly and indirectly communicate his or her intentions to the robot. Additionally, the robot hand needs haptic sensors to control the grip of manipulated objects or to explore the texture of objects. The coupling of hand and arm implies the consideration of both arm and hand within different human robot co-operation schemes and a close co-operation between arm control and hand control.In the following sections we first present our classification of human robot co-operation schemes. The third section features the haptic sensor system and the fourth section describes the control system and interaction of arm, hand, human- robot co-operation module and haptic sensor system.2. Human Robot Co-operationWhen co-operating with a human the behaviour of a robot differs due to the actual task. For example, a robot holding an object manipulated by a human must have another behaviour during this task and in case of an error than a robot holding and leading a human. On the other hand, such a distinction is not always necessary. For example, a robot needs no different way of behaviour when opening a cupboard or a refrigerator. There are different kinds of tasks that need a different behaviour of the robot, whereas other tasks require the same behaviour of a robot. The first step to implementing the different, task dependent ways in robot behaviour is a classification of human robot co-operation schemes.Our classification has been created under the aspect of which situations require different behaviours of the robot. Then this classification has been used to find primitives of interpretation enabling the robot to identify each class by a specific pattern from its sensor data, internal robot data and robot environment. The classification is depicted in Figure 1.Figure 1: Classification of possibilities of Human-Robot-Cooperation.In our classification we first made a distinction whether an additional object is involved in the co-operation or not. If no object is involved there are two classes called leading and restricting. In the class leading the robot is leading the human (e.g. robotic guide dog) or the human is leading the robot (e.g. teaching). This can happen while the robot and the human have a tight connection like a grip or while they have a loose connection like a hand lying on the arm of the co-operation-partner, which results in different kinds of reactions (especially in case of an error) and opens on two new different classes. In the class restricting, the robot restricts the movements of the human (e.g. separating the human from dangerous areas) or the human restricts the movements of the robot (e.g. stopping the robot as a additional concept of safety). This can either be done while the robot and the human are touching each other in a tight grip or - within the class room guardian - while one partner of the co-operation is prohibiting the other form entering an area by crossing his trajectory with parts of his own body in case the other would enter the area. In all classes there is no object directly involved in the co-operation, but this does not mean that there isno object involved at all i.e. a robot can carry an object while it is lead by a human to another place.If there is an object directly involved in the co-operation there are two possible schemes of interaction between human and robot. Either they are just handing over the object or they both manipulate the object at the same time.In case of handing over there is the possibility of a direct handover, which means form hand(s) to hand(s), or the possibility to transfer the object by using a medium. The direct handover requires different ways of behaviour if the object is presented in a fixed configuration that has to be opened during the handover (i.e. a closed hand), or if the object is presented in a way that the other partner of the co-operation can just take the object. These classes can be classified into smaller and more specific classes by focusing of the kind of grip(s) used to hold the object. The handing over of an object by using a medium can be achieved by placing it somewhere in the working space of the partner of the interaction or by throwing (or dropping) it into the partner’s hand.In case of the object manipulation, there are three different classes according to the movement and forces of the participants of the co-operation in aspect to each other. Those can be symmetric, anti-symmetric or independent. In the symmetric case, the movement of the robot and the movement of the human are the same to reach the aim of the co-operative task, like carrying, pushing or pulling something together. In the class anti-symmetric object manipulation the movement of robot and human and the forces generated by them are working against each other. Examples for anti-symmetric object manipulations are things like opening a screw plug or tearing off a piece of paper. If the robot and the human are doing different manipulations on the same object or work on different objects that have a connection to each other, this kind of interaction is found in the class independent object manipulation i.e. filling a glass held by the robot or taking something from a plate carried by the robot.All of the classes have the potential to be split into further subclasses; we already have eleven different classes, most of them resulting in different ways of behaviour of the participants; the behaviour depends on the part of the task done by the robot and by the human, which all in all results in about twenty-two different interactions schemes.The classification of co-operation schemes is basis of the specification of so called interpretation primitives. These primitives combine data and patterns of sensors, the robot, the environment and the human in order to specify and interpret the different steps of a specific co-operation between human and robot. Some of these data are gained by artificial haptic perception.3. Artificial haptic perception: pre-classification of mechanical contactsThe model of the artificial haptic perception is the human sense of touch. It is often considered to consist only of the tactile sense of the skin which is only a part of it. The bathyaesthesia or deep sensibility is also an integral part of this human sense. It includes the senses of force, position and movement of the different parts of the human body [1]. These haptic information –tactile ones and forces- in combination with information about the context of the robot and its environment allow a classification of a detected contact with the environment (Fig. 2 and Fig. 3).In the case of human robot co-operation the class of control contacts is relevant. A contact identified as a control / positioning contact can initialise a co-operation task but the robot needs further information which task is demanded. These information have to be given by other senses e.g. the auditory sense; limiting to haptic perception it would beimaginable to give commands directly using the tactile sense as an input interface which matches defined input patterns with defined commands.In the following classifications a sensor system comprising surface and depth sensibility of a robot is considered. Surface sensibility is achieved by using tactile sensors in foil design applied to the robot arm and hand with different spatial resolution. The palm of the robot hand and the finger tips are supplied with sensors at relevant point to support hand control. Depth sensibility is realised by acceleration sensors and a force torque sensor in the wrist.3.1 Classification of contactsThe main purpose is the classification of contacts according to the quality of intention.We are proposing three classes of contacts which cover all possibilities of interaction between a robot and its environment: collisions , control contacts and task contacts . These main classes can be split in generic sub-classes which can be partly divided again in specific contact patterns e.g. the sub-class grip can be divided in a taxonomy proposed by Cutkosky and Wright [2] with related contact patterns. In Fig. 2 the classes and sub-classes of contacts are shown and will be explained in the following.Collisions can be described as contacts that are not intended at all, neither from the robot nor from its environment. The differentiation of this class in collisions of the robot with humans or objects is making sense if there are different reactions of the robot in such cases.Control contacts are initiated by the robot’s environment with the purpose to give information or commands to the robot. The sub-class positioning is quite near to the model of intuitive human-like interaction because it does not require further information but contacts and forces. Using the tactile sensing as an input interface for defined commands via contact patterns –contacts called command inputs - is not quite that kind of human-like interaction but there are imaginable situations in which it would make sense e.g. in loud environments or simply when the robot does not have other senses.Task contacts are contacts that are related with the actual task of the robot and therefore they are expected and mainly initiated by the robot. In the case of grips these are specific contact patterns for each particular grip. Exploration contacts are initiated by the robot and expected in a certain area of its body e.g. a fingertip but a further differentiation by means of properties to be explored is necessary e.g. the shape of an object.Support describes contacts which are expected as part of a support task e.g. the robot supporting a person with its arm.Figure 2: Contact classes and sub-classes3.2 Parameters of the formal descriptionTo perform a classification a formal description of these contact classes is needed. The parameters on which this description is based include information about the context of the robot-human mechanical contact with environmentcollision task contactcontrol contact grip positioning exploration supportcommand input robot-objectrobot and its environment and, naturally, characteristics of the sensor signals. As seen above in the description of the contact classes appears the quality of intention or expectation so we have chosen the following four parameters concerning the context:Operation mode of the robot: the robot has a task to perform or not (it is active or passive ). When the robot is passive it is in a stand-by-mode and is waiting for an input (“lurking mode”). When it is active it has a task to perform with a related contact pattern (“no contact” represents also a contact pattern e.g. for the task “go from point A to point B”).Expectation of the robot: the perceived contact is expected or not expected. When the robot is active a contact is expected if it is matching the related contact pattern; if not it is unexpected . When the robot is passive all contacts are unexpected . To perform this differentiation the actual contact pattern has to be given to the contact classification unit.Status of the environment: whether there are autonomously moving objects (humans or other robots) in the workspace of the robot (dynamical ) or not (static ). If this information is not available, the default status of the environment has to be dynamical for safety reasons.Intention of environment : a contact can be intended or unintended by the environment.The combination of these four parameters with two possibilities each results in sixteen sets of parameters. Half of these sets do not make sense e.g. a passive robot does not expect any contacts, therefore any contact is unexpected; and to provoke any contact the environment has to be dynamical . In the following diagram (Fig.3) the reasonable combinations with their derived contact classes are shown.Figure 3: Parameter sets of contact classesAs it can be seen, the three contact classes can be distinguished on the basis of these four parameters. The sub-contact classification has to be performed on the basis of the characteristics of the sensor signals.In the case of task contacts the related pattern must be given to the classification unit.A possibility to differentiate collisions of the robot with a human or an object could be the acceleration measured in defined points on the robot. This integration of acceleration sensors in the haptic perception system will be investigated. In the field of robotic control this approach already has been tested [3].In the class control contacts two sub-classes have to be differentiated. The contact patterns for direct input of commands are defined (e.g. in a kind of morse code) but mechanical contact with environmentrobot passive robot activeenvironmentunintended environment intended robot unexpected robot expectedenvironment static environment dynamicalenvironment static environment dynamical environment unintended environment intended environment unintended environment intended collision collision collision task contact control contact control contact task contacttask contact robot unexpected environmentdynamical environment unintended environment unintendedsomehow the input has to be initiated. Using only a part of the robot body as input interface e.g. the back of the hand in combination with an initiation pattern like “three taps” would be a possibility. To recognize a positioning contact the tactile pattern can be used. To lead a robot the user has to grip a part of the robot e.g. the arm. This grip results in a tactile pattern that has opposing areas which would be one possibility to recognize the initiation of a positioning task.Furthermore the classes collision and control contact must be differentiated if environment information is not given. Measurement of accelerations, forces in the joints and the analysis of tactile patterns - whether they are probable for a collision or not - will be investigated.4. Control SystemThe control system of the robot must be specially designed to be able to fulfill the desired tasks. For cooperative tasks the physical interaction between a human and the robot is a key issue. Because robots are usually much stronger and mechanically more robust than a human being, this physical interaction is potentially dangerous for the human. Therefore the control system has to guarantee the safety of the human at all costs.Generally a control system has to perform the three steps 'perceive', 'process' and 'act' to fulfill tasks like object manipulations or movements. But not only a robot performs these steps, but also a human being. While the robot uses its sensors to 'perceive' the human uses his or her senses. The 'processing' is done by software on a microprocessor for the robot while the human uses the central nerve system. And finally the robot 'acts' using actuators like motors and the human uses his or her muscles. For the human-robot-cooperation with physical interaction the acting of the robot is perceived by the human and the acting of the human is perceived by the robot. Therefore the human closes the control loop from acting to perceiving for the robot and vice versa [4].Figure 4 shows the proposed control system for the robot used for the human-robot-cooperation schematically. The approach is based on the 'classical' hierarchical control architecture [5], [6]. The figure also shows the human involved in the cooperation as described in the previous paragraph. At the highest level shown in the figure is the human-robot-cooperation module. This module decides what to do, i.e. how to 'act', according to:•the classification of possibilities of human-robot-cooperation described in section 2•the interpreted sensor data, like e.g. the classification of mechanical contacts described in section 3•context information about the environment from the internal model.The 'acting' commands from the human-robot-cooperation module are then forwarded to the high and low level control of the different actuators. The complete robot planned in this project will consist of a 'body', i.e. a mobile platform, equipped with two arms, two hands and a head. The respective sub-control systems for these sub-systems are not considered here, because their specifics are not relevant for the human-robot-cooperation (see e.g. [7]). For the first phase of the project a simpler mechanical system will be used, consisting of one fixed robot-arm equipped with a humanoid hand with up to 5 independent fingers.The sub-control systems of body, arm and hand control the different actuators of the robot respectively. These mechanical actuators, like motors, pneumatic cylinders etc., physically interact with the human cooperation partner. This interaction can be more or less mechanically direct, as discussed in section 2.The human perceives the acting of the robot with his or her senses, processes the perception and reacts by actuating his or her muscles. This reaction is in turn perceived by the robot with its sensors. To perform the physical interaction safely for the human allrelevant physical sizes must be sensed. Therefore not only the usual position sensors are needed but many additional kinds of sensors, like e.g. tactile, force, torque or acceleration sensors.The raw sensor data must be preprocessed and prepared for further evaluation. This sensor data is then used as feedback signal for the control systems of the body, arms or hands. Additionally the data can be stored in the internal context model of the environment. The preprocessed data is also used to classify the mechanical contacts as discussed in section 3. This step hence interprets the information contained in the sensor data in order to perceive 'what is going on' in the environment. This information can as well be stored in the internal context model of the environment, but is mainly used by the human-robot-cooperation module. This closes the overall control loop.Figure 4: control system for cooperation between robot and human5. ConclusionHuman robot co-operation involves the robot’s perception and interpretation of human actions. For this purpose we have set up a classification of possible human robot co-operation schemes as a basis to design interpretation primitives for robot control; which considers co-operation with or without an object, leading a partner or restricting the movements of a co-operation partner, and the different manners of manipulating the same object at the same time.Closely related to the classification of the human robot co-operation schemes is the classification of the robot’s contacts with its environment, especially considering the intention of the environment and the robot’s expectation of commands according to patterns defined by the interpretation primitives of the human robot co-operation unit. Here,haptic sensors are one of the basic sensor systems to pass the appropriate information and a pre-classification on to the human robot co-operation unit.The present test bed for our research comprises a robot arm and a humanoid hand attached to it as well as different tactile sensors for surface sensibility and haptic sensors for depth sensibility. In our paper we have also presented the concept of the control system involving robot arm, robot hand, human, and the robot’s artificial haptic sensor system.Future work comprises the definition of interpretation primitives for human robot co-operation and the planning and transposition of co-operative tasks. Different sensors are tested and integrated and sensor patterns as well as contact patterns have to be specified. In a later phase of the project further sensors are to be included in the human robot co-operation. All newly designed methods will be tested with our testbed. AcknowledgementThis research was performed at the Institute of Process Control and Robotics, headed by Prof. Dr.-Ing. H. Wörn, at the University of Karlsruhe. The work is being funded by the German Research Foundation, as it is part of the special research program “Humanoid Robots – Learning and Co-operating Systems“. References1Schmidt R.F., Thews G.: ”Physiologie des Menschen”, 27.Aufl., Springer, 1997.2Cutkosky M.R., Wright P.K.: ”Modeling Manufacturing Grips and Correlations with the Design of Robotic Hands”, Proc. IEEE Int. Conf. Robotics and Automation, pp. 1533-1539, 1986.3Stelter J.: “Verbesserung des Positionierverhaltens und der Bahntreue eines Industrieroboters durch den Einsatz von Beschleunigungssensoren”, Shaker Verlag, 2001.4Geiser, G. (1990): Mensch- Maschine-Kommunikation. Oldenbourg Verlag, 1990.5 B. Magnussen, Infrastruktur für Steuerungs- und Regelungssysteme von robotischen Miniatur- undMikrogreifern, Fortschritt-Berichte VDI Reihe 8, Nr.567, Düsseldorf: VDI-Verlag, 1996.6T. Fischer and H. Woern, Structure of a robot system: Karlsruhe Dexterous Hand II, Mediterranean Conference on Control and Systems, 1998.7Dirk Osswald, Heinz Wörn, Mechanical System and Control System of a Dexterous Robot Hand;Proceedings of the IEEE-RAS International Conference on Humanoid Robot, Tokyo, Japan, 2001.。

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设计机器人的英语作文60词

设计机器人的英语作文60词

设计机器人的英语作文60词英文回答：In the realm of advanced technology and human ingenuity, the concept of robots has captured our imaginations for centuries. As we strive to create machines that can assist us in our daily lives and push the boundaries of what is possible, designing a robot requires careful considerationof both form and function.1. Understanding the Purpose and Objectives.The first step in designing a robot is to clearlydefine its intended purpose and objectives. What tasks or functions will it be responsible for? Understanding the specific requirements of the robot is essential fortailoring its design to meet those needs effectively.2. Selecting Suitable Materials and Components.The choice of materials and components used in robot construction depends on the robot's purpose and the environment in which it will operate. Structural components must be robust and durable, while electronic componentsmust be reliable and efficient. Proper materials selection ensures the robot's longevity and performance under various conditions.3. Mechanical Design and Configuration.The mechanical design of a robot involves determiningits kinematics, the arrangement of its joints and actuators, and the overall configuration. Careful consideration mustbe given to factors such as the robot's range of motion, dexterity, and stability. The mechanical design should enable the robot to perform its intended tasks withprecision and efficiency.4. Electrical and Control Systems.The electrical system of a robot provides power and control for its various components. Sensors, actuators, andother subsystems must be integrated seamlessly to ensure proper robot operation. The control system plays a crucial role in coordinating the robot's actions, ensuring smooth and accurate execution of tasks.5. Software Development and Integration.Software development is essential for programming the robot's behavior and controlling its actions. The software must be robust, well-tested, and tailored to the specific purpose of the robot. Software integration involves combining various components of the robot's control system and ensuring their seamless interaction.6. Safety and Reliability Considerations.Designing a robot involves prioritizing safety and reliability throughout the process. Safety features must be incorporated to minimize risks to users and the environment. Reliability measures ensure that the robot can perform consistently under various conditions, minimizing downtime and maintenance requirements.7. Testing and Evaluation.Thorough testing and evaluation are crucial to ensure the robot meets its design specifications and performs as intended. Testing involves evaluating the robot's functionality, accuracy, precision, durability, and safety. Evaluation helps identify areas for improvement and ensures the robot is ready for deployment.中文回答：1.明确目的和目标。

我想要发明一个机器人作文英语

我想要发明一个机器人作文英语

我想要发明一个机器人作文英语I have always been fascinated by the idea of creating a robot that can assist and interact with humans. The concept of artificial intelligence and robotics has captivated my imagination since a young age. As I have grown older, my interest in this field has only deepened, and I have become increasingly determined to turn my dream of inventing a robot into a reality.The primary motivation behind my desire to create a robot stems from a deep-seated belief that such a technology could significantly improve the quality of life for many people. Robots have the potential to perform a wide range of tasks, from the mundane and repetitive to the complex and specialized, with a level of efficiency and precision that often surpasses human capabilities. By developing a robot that can take on these tasks, I hope to free up time and resources for individuals, allowing them to focus on more fulfilling and enriching aspects of their lives.One of the key areas I would like to explore in my robot invention is the field of healthcare. Imagine a robot that could assist elderly ordisabled individuals with daily tasks, such as bathing, dressing, and meal preparation. Such a robot could provide a level of independence and dignity that is often difficult to achieve with traditional caregiving methods. Additionally, a robot could be programmed to monitor the health and well-being of its human counterparts, alerting medical professionals to any concerning changes or issues that arise.Another potential application for my robot invention would be in the realm of education. Imagine a robot that could serve as a personalized tutor, tailoring its teaching methods and content to the specific needs and learning styles of individual students. Such a robot could revolutionize the way we approach education, providing a level of customization and one-on-one attention that is often difficult to achieve in traditional classroom settings.Furthermore, I believe that a robot could be instrumental in advancing scientific research and exploration. Imagine a robot that could be deployed in hazardous or inaccessible environments, gathering data and conducting experiments without putting human lives at risk. Such a robot could be invaluable in fields such as deep-sea exploration, space exploration, and the study of natural disasters.As I contemplate the design and functionality of my robot invention, I am keenly aware of the technical and ethical challenges that mustbe addressed. Ensuring the safety and reliability of the robot is of paramount importance, as is the need to imbue it with a strong ethical framework that prioritizes the well-being of its human counterparts. Additionally, I must consider the potential societal implications of my invention, such as the impact on employment and the need to ensure that the robot does not perpetuate or exacerbate existing inequalities.To tackle these challenges, I plan to draw upon my extensive knowledge of computer science, robotics, and artificial intelligence, as well as my strong problem-solving skills and creative thinking. I will also seek out the guidance and expertise of leading researchers and engineers in the field, collaborating with them to develop a robot that is both technologically advanced and ethically sound.Throughout the development process, I will remain committed to the core principles that have driven my desire to invent a robot in the first place – a desire to improve the lives of others, to push the boundaries of human knowledge and capability, and to create a technology that can be used for the greater good of humanity.As I work towards realizing my dream, I am filled with a sense of excitement and anticipation. The prospect of designing and building a robot that can truly make a difference in the world is a deeply fulfilling and motivating prospect. I am confident that with hard work,dedication, and a relentless pursuit of innovation, I can create a robot that will not only captivate and inspire others, but also make a tangible and positive impact on the world around me.。

BionicCobot敏感辅助人机协作说明书

BionicCobot敏感辅助人机协作说明书

BionicCobotSensitive helper for human-robot collaborationCell Coexistence Synchronised Cooperation Collaboration BionicCobotSensitive helper for human-robot collaborationWhether it is shorter lead times, faster product life cycles or high flexibility with regard to quantities and variety, the requirements of the production of the future are manifold and are changing faster than ever before. This industrial change requires a new way for humans, machines and data to interact.Besides the digital networking of entire facilities, above all robot-based automation solutions, which work hand in hand with peo-ple, play a critical role in this development. In the production of tomorrow, direct interaction between man and machine will be part of the daily routine.Collaborative working spaces of the futureThe strict separation between the manual work of the factory wor-ker and the automated actions of the robot is being increasingly set aside. Their work ranges are overlapping and merging into a collaborative working space. In this way, human and machine will be able to work together on the same workpiece or component simultaneously in future – without having to be shielded from each other for safety reasons. Being at the forefront of industrial automation, it is Festo’s core business to help shape the production and working worlds of the future. A key element for coming up with ideas is the Bionic Lear-ning Network. In an alliance with external partners, Festo looks for natural phenomena and operating principles that can be transfer-red to technology.Paradigm shift in roboticsAt the focus of the current research work are lightweight bionic robots, which due to their natural movement patterns and the pneumatics employed are almost predestined for collaborative working spaces and in future will be able to represent a cost-effective alternative to classic robot concepts.The strengths of pneumatic drives have always lain in their simple handling and robustness, the low costs of acquisition and their high power density – in other words comparatively large forcesin a small space and with a low weight. Holding processes get by without further compressed air consumption and are therefore extremely energy efficient.© Fraunhofer IAO, study of lightweight robots in manual assembly2Festo AG & Co. KGFor direct contact between human and machine, pneumatics offer another critical advantage, however: their system’s inherent flexibi-lity. If an actuator is filled with compressed air, the motion genera-ted can be exactly set in terms of speed, force and rigidity. In the event of a collision, the system eases off, thus posing no risk to the worker.To be able to adjust the whole system to any settings in its dyna-mics, the valve technology used must be able to control the air flows and pressures with extreme precision and at the same time ensure the complex interconnections of many channels.Digitisation of pneumaticsWhat could only be implemented with a great deal of effort until now is made easily possible by a world first from Festo: the Festo Motion Terminal is the first pneumatic automation platform, which, using its software control system, combines the functionalities of over 50 components using apps. Digitisation is opening up com-pletely new areas of application for pneumatics, which until now have been the reserve of electrical automation.Festo Motion Terminal for controlling complex kinematicsThe Festo Motion Terminal combines high-precision mechanics, sensor technology as well as control and measuring technologyin the tightest space. With the internal control algorithms of the Motion Apps and the installed piezo valves, flow rates and pressu-res can be exactly dosed and also varied to any setting in several channels simultaneously. That enables both powerful and fast,as well as soft and sensitive motion sequences.Flexible robot arm with seven degrees of freedomWith the BionicCobot, Festo has now developed a pneumatic light-weight robot with seven degrees of freedom for the first time, which due to this flexibility can work together with humans directly and safely.In terms of its kinematics, the robot is based on the human arm. Like its biological role model, it solves many of its tasks with the help of sensitive movements. Due to its unique drive concept, which works according to the agonist-antagonist principle, the motion dynamics and rigidity can be variably adjusted.01: Collaborative working space: Simul-taneous, common processing of a work-piece by human and robot02: Conceivable future scenario: TheBionicCobot as a supporting assistancesystem in assembly3BionicCobot: Sensitive helper for human-robot collaborationAntagonistAgonistAgonistAntagonistThe natural modelWhether it is gripping powerfully or lifting carefully, pressing firmlyor touching gently – for us humans to be able to execute a movement, the interaction of counteracting muscles is always necessary. This principle of agonist (player) and antagonist (opponent) also influences our daily routine where we perhaps do not even suspect it: we solve many tasks not with precision and accuracy, but do so with flexible and supple movements. If, for example, we put our house key into the door lock, the key finds its destination even without us looking closely at it. If the door is opened from the inside, we automatically give way and follow the movement with appropriate care.The technical implementationBy applying the agonist-antagonist principle, the BionicCobot takes advantage of the natural mechanism of biceps and triceps. The inter-action of flexor and extensor takes place not only in the robot’s upper arm, however, but in all seven joints. There are three axes in its shoul-der area, one each in the elbow and lower arm plus two axes in the wrist. In each axis there is a rotary vane with two air chambers. These form a pair of drives, which can be infinitely adjusted like a mechanical spring by filling them with compressed air.The industrial benefitMode of operation and potential usesFor a safe and more ergonomic future working worldThe BionicCobot is operated intuitively by means of a graphic user interface developed in house. The user can use a tablet to quite easily teach the actions to be performed and set their parameters. In this respect, the defined work steps can be arranged in a time -line in any order using drag and drop. In doing so, the complete motion sequence is virtually depicted and simulated at the same time.Software architecture with three levelsThe interface between the tablet and the Festo Motion Terminal is the ROS (Robot Operating System) open source platform, on which the kinematics’ path planning is calculated. In addition, the ROS interprets the incoming code from the tablet and forwards the resulting axis coordinates to the Motion Terminal.Based on the coordinates received, the Motion Terminal can use its internal algorithms to regulate the respective pressure in the air chambers and hence determine the position of the individual axes. The incoming sensor data from the seven joints is also channelled into the actions in real time.Construction and drive concept based on a natural role model The construction of the BionicCobot is the same as the human arm from the shoulder to upper arm, elbow, ulna and radius down to the wrist and the gripping hand.Like the blood vessels and nerve fibres in the human body, the compressed air lines run safely inside the construction and thus cannot become bent. They supply the pneumatic rotary vane drives, which are located in the seven joints of the robot arm. Installed in each joint are also two pressure sensors and an abso-lute encoder with CAN bus for determining the positional data.If compressed air is supplied to the air chambers in the drives, the rotary vanes move in a certain direction, which is transferred to the integrated bearing shafts. From the elbow downwards, all the lines down to the gripper are laid directly through the shafts. Special packing cartridges enable this rotary through-feed of up to six channels, of which two air lines ultimately supply the gripper. Depending on the task, different gripping systems can be connec -ted to the BionicCobot.6Festo AG & Co. KGThe technical implementation of the agonist-antagonist principle allows the force potential and hence also the rigidity level of the robot arm to be exactly determined. In so-called balancer mode, the BionicCobot is controlled in such a way that it balances gravi-tational force and payload and can calmly hold a desired position immediately. The holding process is done almost without energy and is ideal for assembly activities.Safe collaboration and high user acceptanceApart from the tablet interface, the user also has a manual con-trol panel on the gripping joint at their disposal. The robot can communicate with the user via signals from the blue LED lighting on the joints – for instance to indicate a waiting mode or to send warnings.If, despite this, there is a collision, the robot arm automatically gives way and poses no danger for humans. By using pneumatic semi-rotary drives, the system cannot overheat. In addition, the na-tural movements of the bionic robot arm create a sense of familiarity for the user, which increases acceptance for working together. Many possible applications to relieve humansIn future, the BionicCobot could relieve humans in many places where monotonous and mindless or even dangerous and un-healthy motion sequences are involved. It improves the ergono-mics at the workplace and increases productivity. Particularly in production, manual work, service or maintenance, the pneumatic lightweight robot could be used to partly automate work steps simply and economically.Conceivable future scenariosIn future the system can be flexibly extended and enhanced if required: for instance by adding speech control, image processing, infrared tracking or artificial intelligence. The specially developed software technology, such as the user interface, can also be trans-ferred to other robot kinematics.As the BionicCobot can also work in dirty or unhealthy environ-ments, it is also predestined for use in telemanipulation: with the aid of VR goggles, a person could be made able to control the robot arm as intuitively as his own arm.01: Intuitive operability: The robot arm can easily be taught using the tablet interface 02: Safe handling: The manual controlpanel and one of the LED rings for com-munication with the user03: Sophisticated interaction: The newdrive concept of the seven-axis robotarm027BionicCobot: Sensitive helper for human-robot collaborationTechnical dataDegrees of freedom: (7)Net weight: ..................................................................approx. 6 kg Payload: ...................................................................approx. 1.5 kg Positioning accuracy: .............................................................1 mmSoftware architecture:• User interface: C# WPF application• Calculation and path planning: Robot Operating System (ROS)• Steering and control: Festo Motion TerminalPneumatic drive concept:• 3 pivoting axes, 4 modified rotary axes basedon the DRVS semi-rotary vane drive• 16 compressed air lines• 7 sintered aluminium bearing shafts• 7 adjustable Franke wire race bearings• 15 packing cartridgesDisplacement encoder system:• 14 pressure sensors• 7 absolute encoders with CAN bus• 4 CAN bus cables Project participantsProject initiator:Dr Wilfried Stoll, managing partner,Festo Holding GmbHProject management:Dr Heinrich Frontzek, Dr Elias Knubben,Festo AG & Co. KGProject team:Nadine Kärcher, Mart Moerdijk, Sebastian Schrof, ChristianTrapp, Micha Purucker, Michael Baltes, Nathanael Peltzer,Isabel Lamich, Dr Alexander Hildebrandt, Dr Rüdiger Neumann,Festo AG & Co. KGScientific support:Dr Nina GaißertFesto AG & Co. KGFesto AG & Co. KGRuiter Strasse 8273734 EsslingenGermanyPhone +49 711 347-0Fax +49 711 347-21 55cc@/bionics50133en3/217。

机器人的发展历程英语作文50词

机器人的发展历程英语作文50词

机器人的发展历程英语作文50词Title: The Evolutionary Journey of RoboticsThe history of robots is a tale of innovation and evolution, where the relentless pursuit of efficiency and human-like capabilities has driven technological advancement. From the ancient conceptions of mechanical beings to the present-day intelligent machines, the journey has been one of continuous breakthroughs and revolutionizing impacts on society.In ancient times, myths and legends spoke of bronze men and golems, which can be seen as the precursors to today's robotic concepts. These imaginative stories laid the groundwork for the later development of actual mechanical devices. In the 19th century, with the advent of industrialization, the world witnessed the birth of simple automated machines that could perform repetitive tasks, suchas weaving looms and assembly lines. These early machines, though rudimentary by today's standards, were the foundation upon which modern robotics was built.As the 20th century dawned, the term "robot" was coinedby Karel Čapek in his play R.U.R. (Rossum's Universal Robots), introducing the concept of artificial workers that could replace humans. This sparked a wave of imagination and research into creating more sophisticated machines. It wasn't until the 1950s, however, that the first programmable robot, Unimate, was created by George Devol. Used initially forsimple tasks like lifting and stacking hot pieces of metal on an automobile assembly line, it marked a significantmilestone in the field.The space race of the 1960s and 1970s saw robotics usedfor exploration and extraterrestrial tasks. Robots like Shakey, one of the earliest mobile robots, were developed to navigate complex environments, paving the way for futureautonomous systems. This era also saw the introduction of robots into mainstream entertainment with films andtelevision shows depicting them as integral parts offuturistic societies.The advent of microprocessors in the late 1970s led to a significant decrease in size and cost of electronic components, allowing for the miniaturization of computerized controls within robots. This made them more versatile and adaptable to various applications beyond the manufacturing sector. Robots started to appear in areas such as medicine, agriculture, and even home appliances, becoming moreintegrated into daily life.The 1980s and 1990s were characterized by increased useof robots in industrial settings, with the introduction of more advanced sensors and artificial intelligence techniques. These robots could perform more complex tasks and work alongside human colleagues, improving safety and productivity.During this period, the concept of service robotics also began to take shape, with robots designed to assist in healthcare, education, and customer service industries.The turn of the millennium brought about a new era of robotics with the rise of machine learning and big data analytics. Robots became smarter and more capable of making decisions based on complex algorithms and data inputs. This led to the development of autonomous robots that could navigate without human intervention, such as self-driving cars and drones.The current state of robotics is defined by its integration with Artificial Intelligence (AI). Modern robots are not just mechanical devices; they possess the ability to learn from their environment, make predictions, and interact with humans in a more natural manner. The fields of robotics and AI have merged to create intelligent machines that cancarry out sophisticated tasks, from surgical operations to space exploration, and even companionship for the elderly.Looking ahead, the future of robotics is promising, with ongoing research into areas such as human-robot interaction, soft robotics, and collective behavior in swarm robotics. The goal is to create robots that can seamlessly coexist with humans, enhancing our lives while addressing some of the most pressing challenges of our time.In conclusion, the evolutionary journey of robotics has been a fascinating saga of human ingenuity and technological progress. From the early dreams of mechanical beings to the sophisticated AI-powered machines of today, robots have come a long way. As we continue to push the boundaries of what is possible, the role of robots in our society will undoubtedly become even more profound, shaping a future that promises both excitement and transformation.。