Present and future robot control development—An industrial perspective

Brogårdh, Torgny

doi:10.1016/j.arcontrol.2007.01.002

Cited by 302 publications

(139 citation statements)

References 10 publications

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“…In order to keep and even increase the robot performance in spite of this cost-driven development of the robots, the size of the robot models must grow and more complex multivariable control must be introduced Brogårdh (2007). Up to now the implemented model-based control has been possible to refine such that the requirements have been fulfilled.…”

Section: Model-based Controlmentioning

confidence: 99%

“…Looking into the future of robot control, the cost pressure on robots will for sure proceed, new automation concepts will be needed and robots will be used in new applications Brogårdh (2007). What will happen in a longer perspective is of course difficult to know but some predictions may be possible to give by studying different industry segments.…”

Section: Possible Future Directions Of Robot Control Developmentmentioning

confidence: 99%

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Robot Control Overview: An Industrial Perspective

Brogårdh¹

2009

MIC

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One key competence for robot manufacturers is robot control, defined as all the technologies needed to control the electromechanical system of an industrial robot. By means of modeling, identification, optimization, and model-based control it is possible to reduce robot cost, increase robot performance, and solve requirements from new automation concepts and new application processes. Model-based control, including kinematics error compensation, optimal servo reference-and feed-forward generation, and servo design, tuning, and scheduling, has meant a breakthrough for the use of robots in industry. Relying on this breakthrough, new automation concepts such as high performance multi robot collaboration and human robot collaboration can be introduced. Robot manufacturers can build robots with more compliant components and mechanical structures without loosing performance and robots can be used also in applications with very high performance requirements, e.g., in assembly, machining, and laser cutting. In the future it is expected that the importance of sensor control will increase, both with respect to sensors in the robot structure to increase the control performance of the robot itself and sensors outside the robot related to the applications and the automation systems. In this connection sensor fusion and learning functionalities will be needed together with the robot control for easy and intuitive installation, programming, and maintenance of industrial robots.

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Section: Model-based Controlmentioning

confidence: 99%

Section: Possible Future Directions Of Robot Control Developmentmentioning

confidence: 99%

Robot Control Overview: An Industrial Perspective

Brogårdh¹

2009

MIC

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“…In the past few decades, assembly has been manually completed by workers [1]. Thanks to the rapid development of industrial automation, more and more work is now completed by machines [2].…”

Section: Introductionmentioning

confidence: 99%

Design of Demonstration-Driven Assembling Manipulator

et al. 2018

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Currently, a mechanical arm or manipulator needs to be programmed by humans in advance to define its motion trajectory before practical use. However, the programming is tedious and high-cost, which renders such manipulators unable to perform various different tasks easily and quickly. This article focuses on the design of a vision-guided manipulator without explicit human programming. The proposed demonstration-driven system mainly consists of a manipulator, control box, and camera. Instead of programming of the detailed motion trajectory, one only needs to show the system how to perform a given task manually. Based on internal object recognition and motion detection algorithms, the camera can capture the information of the task to be performed and generate the motion trajectories for the manipulator to make it copy the human demonstration. The movement of the joints of the manipulator is given by a trajectory planner in the control box. Experimental results show that the system can imitate humans easily, quickly, and accurately for common tasks such as sorting and assembling objects. Teaching the manipulator how to complete the desired motion can help eliminate the complexity of programming for motion control.

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“…However, it has a smaller workspace compared to the serial one. A new parallel manipulator similar to Delta called "Tau" with a large cylindrical workspace as with a SCARA robot is also presented [19][20][21]. However, the Tau manipulator consists of three different leg configurations and the kinematic performance is not symmetric.…”

Section: Introductionmentioning

confidence: 99%

Kinematically Redundant Parallel Haptic Device with Large Workspace

Kim

2012

International Journal of Advanced Robotic Systems

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In this paper, a kinematically redundant parallel haptic device with large workspace is presented. The haptic device has a similar kinematic structure to the wellknown Delta manipulator. However, it has a special arrangement of actuators and one redundant actuator added to the third leg. The proposed haptic device has essentially 4-DOF, however, only three translational DOF are used for 3-DOF positioning and force reflection, and one rotational DOF by the redundant actuator is used to increase well-conditioned workspace. If the redundant actuator's angle is controlled to follow x and y position, the haptic device has a large cylindrical workspace and can maintain good kinematic and statics performance over the whole workspace. The kinematics and workspace are analysed, and the optimal design method of finding minimum link lengths to satisfy prescribed workspace is presented. Finally, the prototype haptic device and control experiment result are presented.

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Present and future robot control development—An industrial perspective

Cited by 302 publications

References 10 publications

Robot Control Overview: An Industrial Perspective

Robot Control Overview: An Industrial Perspective

Design of Demonstration-Driven Assembling Manipulator

Kinematically Redundant Parallel Haptic Device with Large Workspace

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