- 上一篇：成形预测级进模冲压件多步展开方法英文文献和中文翻译
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One scenario here is that the teaching ismade by the craftsmen themselves by demonstrations on realobjects using lead through of the robot while vision systems andother sensors collect object features and the robot controllerupdates data bases or other repositories with the rules that willbe used for the robot task execution。 In order to make use ofrules and data from other similar installations the robotcontrollers could be embedded in networks to make use ofexperience and process models generated on other manufactur-ing sites。 Such system support together with the directinteraction between craftsman and robot could give thepossibilities to make future robotics as flexible and easy touse as necessary for the introduction of flexible automation inapplications, where manual work force is the only economic-ally realistic solution today。Beside the more exotic scenarios described above there willof course also be an ongoing development of the robottechnology of today。 This means further optimisation of theperformance/price ratio both with respect to the manufacturingcost of the robots and the life time costs of the robotinstallations。 As discussed earlier robot control is veryimportant in order to get as much performance as possibleout of a robot structure。 Model-based control using accuratemodels from system identification of each inpidual robot willegive the future possibilities to push the performance/price ratiofurther, especially if sensors are introduced in the arm structureof the robot。 However, even with the most accurate control therobot performance cannot surpass the fatigue limits of the robotstructure and its mechanical components and the torque-,current- and temperature limits of the drive system。 Thus, to gofurther in the optimal use of industrial robots these limits mustbe tuned to the tasks of the inpidual robots。 One scenario forthis is to introduce adaptive robot performance。 This means thatthe controller automatically tunes the drive system parametersto optimise the robot performance for the robot programs thatare running。 For this thermal and mechanical fatigue modelsmust be executed together with the dynamic robot models inreal time to estimate temperature and mechanical stress incritical components and structures。 This adaptivity will result inbetter use of the installed robot and moreover it will make therobot design more efficient since it will not be criticallydependent on worst case movements。
5。 ConclusionsIndustrial robot development has for sure not reached itslimits and there is still a lot of work to be done to bridge the gapbetween academic research and industrial development and tointensify academic research in directions that target newapplications and new flexible automation concepts。 Whendeveloping robot control for real industrial use a lot ofunforeseen problems arise and many of these problems needapplied research to be solved。 It is then very important with aclose collaboration between researchers, industrial robotdevelopers, automation system builders and robot users。 Someresearch- and development tasks in the robot control area forsuch collaboration have been outlined in this presentation andthe following is a short summary of the R&D directions thathave been discussed:- Sensor-based robot control for safe interaction betweenhuman and robot and simultaneously for high performancecontrol of low cost robot mechanics。- Sensor-based human–robot interfaces for intuitive robotprogramming and cell calibration。- Efficient scalable software architectures for interactiverobotics。- Tools to be used in robot installations for automaticidentification and tuning of model-based robot controlparameters, especially for highly modular robot mechanics。-
De facto standards and easy to use tools for planning,optimisation, configuring, calibration, programming and re-configuring of robot automation systems。 Important conceptscould be Plug and Play for both virtual and real componentsand knowledge databases for process- and automationdeployment。- Further integration of process control into the robot controller,especially in applications where force/torque sensors and 3Dvision will be used。- Extending model-based control with features for adaptiverobot performance。ReferencesABB-2。 (2001)。 IRB7600 power robot。 http://www。rimrockcorp。com/products/robots/7600/brochures/default。htm。ABB-1。 (2003)。 ABB’s industrial solutions for the automotive industry。 http://www。abb。com/global/seitp/seitp161。nsf/99ad595c32e0c2d9c12566e1000a4540/27b64a329396d49bc1256bf8003588c5/$FILE/Automotive%20Industrial%20IT%20brochure。pdf。ABB-3。 (2004)。 Product specification pickmaster。 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human-friendly robot design。 International Journal ofRobotics Research, 23(4/5), 379–398。Torgny Broga ˚rdh is company senior specialist in mechatronics atABB Robotics。 He got his PhD 1975 for Prof。 Hellmuth Hertz in instru-mentation technology at the University of Lund and became assistantprofessor there in 1976。 Between 1982 and 1986, he was associatedprofessor at the Royal Institute of Technology in Stockholm。 From 1976to 1986, he worked at the ASEA Central Research Laboratory, where hedeveloped new industrial measurement methods and a new fibre opticmeasurement technology。 In 1986, he went to ABB Robotics, where heworks with research in motion control, mechatronic design, sensors andparallel kinematics。 He is a member of the research board CENIIT at theUniversity of Linko ¨ping and a member of the Swedish Foundation ofStrategic Research。 In 1998, he got the Swedish Royal Academy ofEngineering gold medal for his contributions to the robotics developmentat ABB。源`自'751`.论"文|网[www.751com.cn